A hybrid few-shot multiple-instance learning model predicting the aggressiveness of lymphoma in PET/CT images

BACKGROUND AND OBJECTIVE

Patients with aggressive non-Hodgkin lymphoma (NHL) undergo distinct therapy strategies compared with indolent NHL patients. However, it is challenging to estimate NHL aggressiveness based on visual inspection of positron emission tomography (PET) or computed tomography (CT) images. Since diffuse large B-cell lymphoma (DLBCL) and Follicular lymphoma (FL) are the most typical and dominant aggressive and indolent NHL, respectively, this study aims to develop an artificial-intelligence-enabled model to distinguish DLBCL from FL in PET/CT images as the first step to tackle this challenge.

METHODS

We propose a hybrid few-shot multiple-instance learning model to predict the aggressiveness of the NHL. First, rotation-based self-supervision learning (SSL) has been employed to train the encoder on a large-scale, publicly available CT image dataset. Second, hybrid instance-level features are obtained for each NHL lesion by combining deep features with the radiomics features from both PET and CT modalities. Third, instance-level features are transformed into bag-level (or patient-level) representations. Finally, bag-level representations are fed into a distance-based classifier through few-shot learning to predict NHL aggressiveness.

RESULTS

Our model achieves an accuracy of 0.751 ± 0.008, a sensitivity of 0.787 ± 0.012, a specificity of 0.715 ± 0.013, an F1-score of 0.753 ± 0.009, and an area under the curve (AUC) of 0.795 ± 0.009 at the bag level. It outperforms the typical counterparts that use the radiomic features, random forest for feature selection, and support vector machines (SVMs) as classifiers. The three counterparts yield accuracies of 0.714 ± 0.023, 0.705 ± 0.008, and 0.698 ± 0.008, respectively. Moreover, settings of the SSL training dataset (Deep lesion) and task (rotation), hybrid CT and radiomic PET features, the pool-layer strategy of maximum, and distance-based classifier generate the best model.

CONCLUSIONS

A hybrid few-shot multiple-instance learning model can predict lymphoma aggressiveness in PET/CT images and could be a potential tool for determining therapy strategies. Hybrid features and the combination of SSL, few-shot learning, and weakly supervised learning are the two powerful pillars of the model, and these can be expanded to other medical applications with limited samples and incomplete annotations.

PGF2α induces a pro-labour phenotypical switch in human myometrial cells that can be inhibited with PGF2α receptor antagonists

Preterm birth is the leading cause of infant morbidity and mortality. There has been an interest in developing prostaglandin F2α (PGF2α) antagonists as a new treatment for preterm birth, although much of the rationale for their use is based on studies in rodents where PGF2α initiates labour by regressing the corpus luteum and reducing systemic progesterone concentrations. How PGF2α antagonism would act in humans who do not have a fall in systemic progesterone remains unclear. One possibility, in addition to an acute stimulation of contractions, is a direct alteration of the myometrial smooth muscle cell state towards a pro-labour phenotype. In this study, we developed an immortalised myometrial cell line, MYLA, derived from myometrial tissue obtained from a pregnant, non-labouring patient, as well as a novel class of PGF2α receptor (FP) antagonist. We verified the functionality of the cell line by stimulation with PGF2α, resulting in Gαq-specific coupling and Ca2+ release, which were inhibited by FP antagonism. Compared to four published FP receptor antagonists, the novel FP antagonist N582707 was the most potent compound [Fmax 7.67 ± 0.63 (IC50 21.26 nM), AUC 7.30 ± 0.32 (IC50 50.43 nM), and frequency of Ca2+ oscillations 7.66 ± 0.41 (IC50 22.15 nM)]. RNA-sequencing of the MYLA cell line at 1, 3, 6, 12, 24, and 48 h post PGF2α treatment revealed a transforming phenotype from a fibroblastic to smooth muscle mRNA profile. PGF2α treatment increased the expression of MYLK, CALD1, and CNN1 as well as the pro-labour genes OXTR, IL6, and IL11, which were inhibited by FP antagonism. Concomitant with the inhibition of a smooth muscle, pro-labour transition, FP antagonism increased the expression of the fibroblast marker genes DCN, FBLN1, and PDGFRA. Our findings suggest that in addition to the well-described acute contractile effect, PGF2α transforms myometrial smooth muscle cells from a myofibroblast to a smooth muscle, pro-labour-like state and that the novel compound N582707 has the potential for prophylactic use in preterm labour management beyond its use as an acute tocolytic drug.

Spatial and temporal distribution of endotoxins, antibiotic resistance genes and mobile genetic elements in the air of a dairy farm in Germany

Antimicrobial resistance (AMR) is a serious issue that is continuously growing and spreading, leading to a dwindling number of effective treatments for infections that were easily treatable with antibiotics in the past. Animal farms are a major hotspot for AMR, where antimicrobials are often overused, misused, and abused, in addition to overcrowding of animals. In this study, we investigated the risk of AMR transmission from a farm to nearby residential areas by examining the overall occurrence of endotoxins, antibiotic resistance genes (ARGs), and mobile genetic elements (MGEs) in the air of a cattle farm. We assessed various factors, including the season and year, day and nighttime, and different locations within the farm building and its vicinity. The most abundant ARGs detected were tetW, aadA1, and sul2, genes that encode for resistances towards antibiotics commonly used in veterinary medicine. While there was a clear concentration gradient for endotoxin from the middle of the farm building to the outside areas, the abundance of ARGs and MGEs was relatively uniform among all locations within the farm and its vicinity. This suggests that endotoxins preferentially accumulated in the coarse particle fraction, which deposited quickly, as opposed to the ARGs and MGEs, which might concentrate in the fine particle fraction and remain longer in the aerosol phase. The occurrence of the same genes found in the air samples and in the manure indicated that ARGs and MGEs in the air mostly originated from the cows, continuously being released from the manure to the air. Although our atmospheric dispersion model indicated a relatively low risk for nearby residential areas, farm workers might be at greater risk of getting infected with resistant bacteria and experiencing overall respiratory tract issues due to continuous exposure to elevated concentrations of endotoxins, ARGs and MGEs in the air of the farm.

Depicting and predicting changes of lung after lobectomy for cancer by using CT images

Lobectomy is an effective and well-established therapy for localized lung cancer. This study aimed to assess the lung and lobe change after lobectomy and predict the postoperative lung volume. The study included 135 lung cancer patients from two hospitals who underwent lobectomy (32, right upper lobectomy (RUL); 31, right middle lobectomy (RML); 24, right lower lobectomy (RLL); 26, left upper lobectomy (LUL); 22, left lower lobectomy (LLL)). We initially employ a convolutional neural network model (nnU-Net) for automatically segmenting pulmonary lobes. Subsequently, we assess the volume, effective lung volume (ELV), and attenuation distribution for each lobe as well as the entire lung, before and after lobectomy. Ultimately, we formulate a machine learning model, incorporating linear regression (LR) and multi-layer perceptron (MLP) methods, to predict the postoperative lung volume. Due to the physiological compensation, the decreased TLV is about 10.73%, 8.12%, 13.46%, 11.47%, and 12.03% for the RUL, RML, RLL, LUL, and LLL, respectively. The attenuation distribution in each lobe changed little for all types of lobectomy. LR and MLP models achieved a mean absolute percentage error of 9.8% and 14.2%, respectively. Radiological findings and a predictive model of postoperative lung volume might help plan the lobectomy and improve the prognosis.

Pulse Oximetry and Perfusion Index Screening for Congenital Heart Defects: A Systematic Review and Meta-analysis

Congenital heart defects (CHDs) are the most common neonatal malformations and are a leading cause of infant death in developed countries. Finding safe and effective diagnostic methods to screen for CHDs is important. The aim of this study was to evaluate the effectiveness of pulse oximetry (PO) and perfusion index (PI) in screening CHD. We conducted a systematic review of studies in PubMed, Embase, and the Cochrane Library published on or before October 1, 2021. Studies based on PICOS were included in this systematic review. The flow chart is made by PRISMA software. The quality of included studies was assessed by RevMan5 software (QUADAS-2: Quality Assessment of Diagnostic Accuracy Studies-2). The sensitivity, specificity, and other measurements of accuracy were pooled using Stata/SE 12.0 software. Five studies containing 46,965 neonates were included in this study. A randomized-effects model was used for the meta-analysis because of significant heterogeneity. The combined sensitivity and specificity were 0.82 (95% confidence interval [CI], 0.53-0.95) and 0.97 (95% CI, 0.57-1.00), respectively. The area under the curve was 0.92 (95% CI, 0.89-0.94). The combination PO and PI was significant in CHD screening. Once diagnosed by the combined method, it means that the neonate is most likely to have a CHD. KEY POINTS: · Pulse oximetry and PI screening.. · Congenital heart defects.. · A systematic review and meta-analysis..

Nomograms integrating CT radiomic and deep learning signatures to predict overall survival and progression-free survival in NSCLC patients treated with chemotherapy

OBJECTIVES

This study aims to establish nomograms to accurately predict the overall survival (OS) and progression-free survival (PFS) in patients with non-small cell lung cancer (NSCLC) who received chemotherapy alone as the first-line treatment.

MATERIALS AND METHODS

In a training cohort of 121 NSCLC patients, radiomic features were extracted, selected from intra- and peri-tumoral regions, and used to build signatures (S1 and S2) using a Cox regression model. Deep learning features were obtained from three convolutional neural networks and utilized to build signatures (S3, S4, and S5) that were stratified into over- and under-expression subgroups for survival risk using X-tile. After univariate and multivariate Cox regression analyses, a nomogram incorporating the tumor, node, and metastasis (TNM) stages, radiomic signature, and deep learning signature was established to predict OS and PFS, respectively. The performance was validated using an independent cohort (61 patients).

RESULTS

TNM stages, S2 and S3 were identified as the significant prognosis factors for both OS and PFS; S2 (OS: (HR (95%), 2.26 (1.40-3.67); PFS: (HR (95%), 2.23 (1.36-3.65)) demonstrated the best ability in discriminating patients with over- and under-expression. For the OS nomogram, the C-index (95% CI) was 0.74 (0.70-0.79) and 0.72 (0.67-0.78) in the training and validation cohorts, respectively; for the PFS nomogram, the C-index (95% CI) was 0.71 (0.68-0.81) and 0.72 (0.66-0.79). The calibration curves for the 3- and 5-year OS and PFS were in acceptable agreement between the predicted and observed survival. The established nomogram presented a higher overall net benefit than the TNM stage for predicting both OS and PFS.

CONCLUSION

By integrating the TNM stage, CT radiomic signature, and deep learning signatures, the established nomograms can predict the individual prognosis of NSCLC patients who received chemotherapy. The integrated nomogram has the potential to improve the individualized treatment and precise management of NSCLC patients.

Dose Coverage Variation Caused by Setup Uncertainties in VMAT-TBI Treatment

PURPOSE/OBJECTIVE(S)

Volumetric Modulated Arc Therapy Total Body Irradiation (VMAT TBI) offers several advantages over conventional TBI techniques, including reduced cost of the treatment room (a normal-sized vault versus a large shielded vault), increased patient comfort during treatment, lung sparing without the need for physical blocks, and a more homogeneous dose distribution. In VMAT-TBI treatment, plans at multiple isocenters are utilized to cover the entire body, and patients are positioned with the aid of image guidance. However, aligning the patient's entire body during setup can be challenging due to its pliability, and the setup time is heavily dependent on the tolerance allowed by the image guidance. Therefore, studying the variation in dose coverage caused by setup uncertainties in VMAT-TBI treatments can help optimize the clinical workflow and determine the optimal tolerance for patient positioning.

MATERIALS/METHODS

New plans were generated to simulate the uncertainties that occur during treatment setup for each patient. These plans were created by shifting the original VMAT TBI plans at the head, chest, abdomen (or pelvis) isocenters by 5mm and 1cm in the left-right (LR), inferior-superior (IS), and anterior-posterior (AP) directions, respectively. Dose DicomRT files were exported, and the dose change due to the shifts was analyzed. The statistical quantification of the percentage of the body that experienced a dose change of over 2%, 5%, and 10% of the prescription due to the shifts from the original plans was calculated for all patients. Histograms were generated, showing the percentage of body getting dose change of 1-2%, 2-3%, 3-5%, 5-7%, 7-10%, 10-15%.

RESULTS

The table below displays the percent volume receiving a dose change of 2%, 5%, and 10% of the prescription for a 5mm shift. Among the shift directions, the dose change is most sensitive in the IS direction, with similar impact observed the in LR and AP directions. Among different sites, the chest experiences the largest dose change, followed by the pelvis. For a 5mm shift in the IS direction, the average percent volume receiving a dose change of 2%, 5%, and 10% in the chest is 9.25%, 2.64%, and 0.27%, respectively. For a 1cm shift, the numbers are 12.23%, 6.75%, and 1.29%. In the pelvis (abdomen), these values are 9.03%, 1.67%, and 0.17% for a 5mm shift and 13.28%, 6.1%, and 0.85% for a 1cm shift. For head plans, the values are 2.72%, 0.9%, and 0.14% for a 5mm shift and 3.77%, 1.66%, and 0.53% for a 1cm shift.

CONCLUSION

Accurate alignment in the chest region is crucial in VMAT TBI treatment. Efforts should be made to minimize shifts over 1cm in the IS direction.

Dosimetric Impact of Seed Segmentation in GammaTile Surgically Targeted Radiation Therapy for Gliomas and Brain Metastases Cases

PURPOSE/OBJECTIVE(S)

To assess the variability of dose reporting variability due to uncertainty in segmentation of Cs-131 seeds in GammaTile therapy for gliomas and brain metastases.

MATERIALS/METHODS

Ten patients with either glioma or brain metastases had 4-11 GammaTiles placed along resection bed during craniotomy. A dose of 60 Gy is prescribed to 5 mm depth. Each GammaTile has four Cs-131 seeds imbedded in a biodegradable collagen sponge. GammaTile Post-Op workflow in MIM Symphony software is used for post-implant dose evaluation and reporting. This workflow requires a post-surgery CT to identify seeds, and a post-surgery MR for residual disease and OAR contours. Seeds are segmented using a threshold tool. Threshold levels may change depending on the CT used, thus users need to manually change the HU threshold value in each data set. Since GammaTiles are lined along the resection bed, PTVs are generated automatically by adding 8 mm expansion on the seed contours and later combined with residual disease contours. We simulate the seed contour uncertainty by applying -0.5 mm, -1.0 mm, +0.5 mm & +1.0 mm concentric margins to the current seed contours to create 4 new seed contours per patient. New PTVs are generated by adding 8 mm expansion on the new seed contours combined with residual disease contours. PTV volume, PTV volume receiving 100% and 150% of prescription dose (V100, V150), and percentage of the prescription dose received by 90% of the PTV (D90) are calculated to evaluate dose reporting variability due to seed segmentation uncertainty.

RESULTS

Mean PTV volume decreases by 8.4 cc & 10.2 cc for PTVs generated from seed contours with -0.5 mm & -1.0 mm margin, respectively, and increases by 5.8 cc & 8.2 cc, respectively, when +0.5 mm & +1 mm margins are applied to the original seed contours. We observe up to 10% change in V100 due to seed segmentation uncertainty. Mean V100 increases by 4.0% (range: 0.2% - 8.9%) & 4.9% (range: 0.5% - 11.0%) for cases with -0.5 m & -1.0 mm seed margin, respectively, and reduces by 4.2% (range: 0.5% - 6.7%) & 5.9% (range: 0.6% - 10.4%) for cases with +0.5 mm and +1.0 mm seed margin, respectively. Mean D90 increases by 7.7% (range: 4.0% - 12.6%) & 9.9% (range: 4.0% - 17.4%) for cases with -0.5 m & -1.0 mm seed margin, respectively, and reduces by 5.5% (range: 3.6% - 7.8%) & 7.4% (range: 5.2% - 9.6%) for cases with +0.5 mm and +1.0 mm seed margin, respectively. We also observe up to 8.0% changes in mean V150 when margins are applied to the seed contours.

CONCLUSION

Our results show significant impact of seed segmentation uncertainty on dose reporting in GammaTile therapy. Variability in dose reporting parameters highlight the need for a more standardized and automated approach to seed segmentation to ensure consistent and accurate dose reporting. The current manual threshold adjustment method is subject to user dependence and therefore unreliable. Development of a more robust tool could help to minimize variability and improve reliability of dose reporting.

Coixendide efficacy in combination with temozolomide in glioblastoma and transcriptome analysis of the mechanism

The purpose of this study was to explore the role of coixendide (Coix) combine with temozolomide (TMZ) in the treatment of Glioblastoma (GBM) and explore its possible mechanism. CCK-8 was used to determine the inhibitory rate of Coix group, TMZ group and drug combination group on GBM cells, and the combination index (CI) was calculated to determine whether they had synergistic effect. Then RNA was extracted from each group, transcriptome sequencing was performed, and differentially expressed genes (DEGs) were identified. The possible mechanism was analyzed by GO enrichment analysis and KEGG enrichment analysis. The CI of Coix and TMZ indicating a synergistic effect when TMZ concentration is 0.1 mg/ml and Coix concentration is 2 mg/ml. Transcriptome sequencing analysis showed that interferon (IFN) related genes were down-regulated by Coix and up-regulated by TMZ and combined drugs, however, the up-regulation induced by combined drugs was less than that of TMZ. Besides IFN related genes, cholesterol metabolism pathway were also been regulated. Coix and TMZ have synergistic effects in the treatment of GBM at certain doses. RNA-Seq results suggested that the abnormal on genetic materials caused by DNA damage induced by TMZ treatment can be sensed by IFN related genes and activates antiviral IFN signaling, causing the activation of repairing mechanism and drug resistance. Coix inhibits IFN related genes, thereby inhibits drug resistance of TMZ. In addition, the activation of ferroptosis and the regulation of DEGs in cholesterol metabolism pathway were also contributed to the synergistic effects of Coix and TMZ.

Probable Evidence of Aerosol Transmission of SARS-COV-2 in a COVID-19 Outbreak of a High-Rise Building

Although it is well established that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can be transmitted through aerosols, the mode of long-range aerosol transmission in high-rise buildings remains unclear. In this study, we analyzed an outbreak of coronavirus disease 2019 (COVID-19) that occurred in a high-rise building in China. Our objective was to investigate the plausibility of aerosol transmission of SARS-CoV-2 by testing relevant environmental variables and measuring the dispersion of a tracer gas in the drainage system of the building. The outbreak involved 7 infected families, of which 6 were from vertically aligned flats on different floors. Environmenìtal data revealed that 3 families' bathrooms were contaminated by SARS-CoV-2. In our tracer experiment, we injected tracer gas (CO₂) into the dry floor drains and into water-filled toilets in the index case' s bathroom. Our findings showed that the gas could travel through vertical pipes by the dry floor drains, but not through the water of the toilets. This indicates that dry floor drains might facilitate the transmission of viral aerosols through the sewage system. On the basis of circumstantial evidence, long-range aerosol transmission may have contributed to the community outbreak of COVID-19 in this high-rise building. The vertical transmission of diseases through aerosols in high-rise buildings demands urgent attention.

pH Dependence of a GPR4 Selective Antagonist Hampers Its Therapeutic Potential

Inflammatory bowel disease (IBD) is characterized by chronic mucosal inflammation of the gastrointestinal tract and is associated with extracellular acidification of mucosal tissue. Several extracellular pH-sensing receptors, including G protein-coupled receptor 4 (GPR4), play an important role in the regulation of inflammatory and immune responses, and GPR4 deficiency has been shown to be protective in IBD animal models. To confirm the therapeutic potential of GPR4 antagonism in IBD, we tested Compound 13, a selective GPR4 antagonist, in the interleukin 10-/- mouse model of colitis. Despite good exposures and albeit there was a trend toward improvement for a few readouts, Compound 13 treatment did not improve colitis in this model, and there were no signs of target engagement. Interestingly, Compound 13 behaved as an "orthosteric" antagonist, i.e., its potency was pH dependent and mostly inactive at pH levels lower than 6.8 with preferential binding to the inactive conformation of GPR4. Mutagenesis studies confirmed Compound 13 likely binds to the conserved orthosteric binding site in G protein-coupled receptors, where a histidine sits in GPR4 likely preventing Compound 13 binding when protonated in acidic conditions. While the exact mucosal pH in the human disease and relevant IBD mice models is unknown, it is well established that the degree of acidosis is positively correlated with the degree of inflammation, suggesting Compound 13 is not an ideal tool to study the role of GPR4 in moderate to severe inflammatory conditions. SIGNIFICANCE STATEMENT: Compound 13, a reported selective GPR4 antagonist, has been widely used to assess the therapeutic potential of GPR4, a pH-sensing receptor, for numerous indications. Its pH dependence and mechanism of inhibition identified in this study clearly highlights the limitations of this chemotype for target validation.

Deep radiomic model based on the sphere-shell partition for predicting treatment response to chemotherapy in lung cancer

BACKGROUND

The prognosis of chemotherapy is important in clinical decision-making for non-small cell lung cancer (NSCLC) patients.

OBJECTIVES

To develop a model for predicting treatment response to chemotherapy in NSCLC patients from pre-chemotherapy CT images.

MATERIALS AND METHODS

This retrospective multicenter study enrolled 485 patients with NSCLC who received chemotherapy alone as a first-line treatment. Two integrated models were developed using radiomic and deep-learning-based features. First, we partitioned pre-chemotherapy CT images into spheres and shells with different radii around the tumor (0-3, 3-6, 6-9, 9-12, 12-15 mm) containing intratumoral and peritumoral regions. Second, we extracted radiomic and deep-learning-based features from each partition. Third, using radiomic features, five sphere-shell models, one feature fusion model, and one image fusion model were developed. Finally, the model with the best performance was validated in two cohorts.

RESULTS

Among the five partitions, the model of 9-12 mm achieved the highest area under the curve (AUC) of 0.87 (95% confidence interval: 0.77-0.94). The AUC was 0.94 (0.85-0.98) for the feature fusion model and 0.91 (0.82-0.97) for the image fusion model. For the model integrating radiomic and deep-learning-based features, the AUC was 0.96 (0.88-0.99) for the feature fusion method and 0.94 (0.85-0.98) for the image fusion method. The best-performing model had an AUC of 0.91 (0.81-0.97) and 0.89 (0.79-0.93) in two validation sets, respectively.

CONCLUSIONS

This integrated model can predict the response to chemotherapy in NSCLC patients and assist physicians in clinical decision-making.

Arthroscopic vs. open Broström-Gould for repairing anterior talofibular ligament: mid-term outcomes comparison

Introduction

There have been few mid-term follow-up studies comparing arthroscopic and open Broström-Gould repair of the anterior talofibular ligament (ATFL). The purpose of this study was to evaluate the mid-term therapeutic effectiveness of arthroscopic ATFL repair with open Broström-Gould repair for chronic lateral ankle instability.

Methods

We retrospectively reviewed the database of patients with chronic lateral ankle instability undergoing repair of the ATFL from June 2014 to June 2018. The choice of surgical approach will depend on computer-generated randomization. In total, 49 patients underwent the arthroscopic Brostrom-Gould technique (group AB), while the other 50 patients underwent the open Broström-Gould technique (group OB). The surgery duration, hospitalization time, postoperative complications, the preoperative/postoperative manual anterior drawer test (ADT), Visual analog scale (VAS) scores, American Orthopaedic Foot & Ankle Society (AOFAS) scores, Karlsson-Peterson (K-P) scores, and Tegner activity scores were collected for comparative analysis during the follow-up period of 48 months.

Results

At the final follow-up, the clinical outcomes, including ADT, VAS, AOFAS, K-P, and Tegner activity scores, were significantly improved after either arthroscopic or open treatment. Specifically, the AOFAS and K-P scores in the group AB were significantly higher than those in the group OB at 6 months post-surgery (P < 0.05). Additionally, there were no significant differences in other clinical outcomes and postoperative complications between the two groups.

Conclusions

Arthroscopic has predictable and good mid-term results after ATFL and may be a secure and effective alternative to open Broström-Gould repair.

Two Secretory T2 RNases Act as Cytotoxic Factors Contributing to the Virulence of an Insect Fungal Pathogen

RNase T2 members are secreted by several pathogens or parasites during infection, playing various roles in pathogen-host interaction. However, functions of those members in biocontrol microbes targeting their hosts are still unknown. Here, we report that an insect fungal pathogen, Beauveria bassiana, produces two secretory RNase T2 members that act as cytotoxic factors, which were examined by insect bioassays using the targeted gene(s) disruption and overexpression strains. Overexpression strains displayed dramatically increased virulence, which was concurrent with few fungal cells and hemocytes in hemocoel, suggesting a cytotoxicity of the overexpressed gene products. In vitro assays using yeast-expressed proteins verified the cytotoxicity of the two members against insect cells, to which the cytotoxic effect was dependent on their RNases enzyme activities and glycosylation modification. Moreover, the excessive humoral immune responses triggered by the two ribonucleases were examined. These results suggested prospects of these two T2 ribonucleases for improvement of biocontrol agents.

Size dependent effects of nanoplastics and microplastics on the nitrogen cycle of microbial flocs

NANO: and microplastics (NPs/MPs) are a new type of persistent environmental pollutant. Microbial flocs are a type of microbial aggregate commonly used in aquaculture. To investigate the impact of NPs/MPs on microbial flocs with different particle sizes: NPs/MPs-80 nm (M 0.08), NPs/MPs-800 nm (M 0.8), and NPs/MPs-8 μm (M 8), NPs/MPs exposure tests (28 days) and ammonia nitrogen conversion tests (24 h) were conducted. The results showed that the particle size was significantly higher in the M 0.08 group when compared with the control group (C group). The TAN (total ammonia nitrogen) content of each group maintained the order of M 0.08 > M 0.8 > M 8 > C from days 12-20. The nitrite content in the M 0.08 group was significantly higher on day 28 than that in the other groups. In the ammonia nitrogen conversion test, the nitrite content of the C group was significantly lower than that of the NPs/MPs exposure groups. The results suggested that NPs contributed to microbial aggregation and affected microbial colonization. In addition, NPs/MPs exposure could reduce microbial nitrogen cycling capacity, with a size-dependent toxicity difference of NPs > MPs. The findings of this study are expected to fill the research gap on the mechanisms of NPs/MPs' impact on microorganisms and the nitrogen cycle in aquatic ecosystems.

Dosimetric Impact of Source Displacement in GammaTile Surgically Targeted Radiation Therapy for Gliomas

Background This study aims to evaluate dosimetric changes that happened during the first month after GammaTile surgically targeted radiation therapy (STaRT) for gliomas due to Cesium-131 (Cs-131) seed displacement caused by cavity shrinkage in brain brachytherapy. Methodology In this study, 10 glioma patients had 4-11 GammaTiles placed along the resection bed after maximal safe resection during craniotomy. Each GammaTile is composed of four Cs-131 seeds embedded in a biodegradable collagen sponge to minimize seed movement and maintain seed-to-cavity surface distance. The Cs-131 seed positions were identified using VariSeed on day one. On day 30, post-implant computed tomography (CT) images and dosimetry parameters were calculated. An iterative closest point (ICP) algorithm was used to compute rigid transformation between the day one and day 30 seed clouds. The seed displacement was calculated after registration. The volume receiving 100% of the prescription dose (V100), the dose received by 90% of the planning target volume (D90_PTV), the planning target volume receiving 100% of the prescription dose (V100_PTV), and the dose to organs at risk (OARs) were calculated for both CT images to determine the dosimetric changes from any seed displacement. Results The mean seed displacement of 1.8 ± 1.0 mm for all patients was observed between day one and day 30. The maximum seed displacement for each patient ranged from 2.3 mm to 7.3 mm. The mean V100 difference between day one and day 30 was 2.5 cc (range = 0.5-6.5 cc). The mean D90_PTVs were 95.5% (range = 69.0%-131.0%) and 98.1% (range = 19.9%-149.0%) on day one and day 30, respectively. The mean V100_PTVs were 88.4% (range = 81.3%-99.1%) and 87.9% (range = 47.0%-99.7%) on day one and day 30, respectively. On day one, the brainstem dose was 63.5 Gy for one case and 28.1 Gy for another case; while on day 30, the brainstem dose was 55.8 Gy and 20.6 Gy for the same patients, contributing to 7.7 Gy (12.8%) and 7.5 Gy (12.5%) dose reductions to brainstem for these patients, respectively. Only two patients received a dose to the optic nerves (34.1 Gy and 5.2 Gy). There were small changes (1.8 Gy and 0.5 Gy, respectively) in the dose to optic nerves when comparing the dose calculated on day one and the dose calculated on day 30 CT images. The same two patients received 30.4 Gy and 6.8 Gy to the chiasm, respectively. Small changes in the dose to the chiasm (≤1.1 Gy) were noted between day one and day 30. Conclusions A maximum seed displacement of up to 7.3 mm and a mean seed displacement of 1.8 mm caused by cavity shrinkage were observed during the first month after GammaTile STaRT for gliomas. There were noticeable changes in dosimetry parameters. Changes in the doses to OARs, particularly the brainstem, were large (up to 12.8% of the prescription dose). These changes in dosimetry should be considered when evaluating treatment outcomes and planning future GammaTile treatments.

Spectral Dual-Layer Computed Tomography Can Predict the Invasiveness of Ground-Glass Nodules: A Diagnostic Model Combined with Thymidine Kinase-1

OBJECTIVES

Few studies have explored the use of spectral dual-layer detector-based computed tomography (SDCT) parameters, thymidine kinase-1 (TK1), and tumor abnormal protein (TAP) for the detection of ground-glass nodules (GGNs). Therefore, we aimed to evaluate the quantitative and qualitative parameters generated from SDCT for predicting the pathological subtypes of GGN-featured lung adenocarcinoma combined with TK1 and TAP.

MATERIAL AND METHODS

Between July 2021 and September 2022, 238 patients with GGNs were retrospectively enrolled in this study. SDCT and tests for TK1 and TAP were performed preoperatively, and the lesions were divided into glandular precursor lesions (PGL), minimally invasive adenocarcinoma (MIA), and invasive adenocarcinoma (IAC), according to the pathological results. A receiver operating characteristic (ROC) curve was used to compare the diagnostic performance of these parameters. Multivariate logistic regression analysis was performed to construct a joint diagnostic model and create a nomogram.

RESULTS

This study included 238 GGNs, including 41 atypical adenomatous hyperplasias (AAH), 62 adenocarcinomas in situ (AIS), 49 MIA, and 86 IAC, with a high proportion of women, non-smokers, and pure ground-glass nodule (pGGN). CT100 keV (a/v), electronic density (EDW) (a/v), Daverage, Dsolid, TK1, and TAP of MIA and IAC were higher than those of PGL. The effective atomic number (Zeff (a/v)) was lower in MIA and IAC than in PGL (all p < 0.05). Logistic regression analysis showed that Zeff (a), EDW (a), TK1, Daverage, and internal bronchial morphology were crucial factors in predicting the aggressiveness of GGN. Zeff (a) had the highest diagnostic performance with an area under the ROC curve (AUC) = 0.896, followed by EDW (a) (AUC = 0.838) and CT100 keVa (AUC = 0.819). The diagnostic model and nomogram constructed using these five parameters (Zeff (a) + EDW (a) + CT100 keVa + Daverage + TK1) had an AUC = 0.933, which was higher than the individual parameters (p < 0.05).

CONCLUSIONS

Multiple quantitative and functional parameters can be selected based on SDCT, especially Zeff (a) and EDW (a), which have high sensitivity and specificity for predicting GGNs' invasiveness. Additionally, the combination of TK1 can further improve diagnostic performance, and using a nomogram is helpful for individualized predictions.

Spectral CT-based radiomics signature for distinguishing malignant pulmonary nodules from benign

OBJECTIVES

To evaluate the discriminatory capability of spectral CT-based radiomics to distinguish benign from malignant solitary pulmonary solid nodules (SPSNs).

MATERIALS AND METHODS

A retrospective study was performed including 242 patients with SPSNs who underwent contrast-enhanced dual-layer Spectral Detector CT (SDCT) examination within one month before surgery in our hospital, which were randomly divided into training and testing datasets with a ratio of 7:3. Regions of interest (ROIs) based on 40-65 keV images of arterial phase (AP), venous phases (VP), and 120kVp of SDCT were delineated, and radiomics features were extracted. Then the optimal radiomics-based score in identifying SPSNs was calculated and selected for building radiomics-based model. The conventional model was developed based on significant clinical characteristics and spectral quantitative parameters, subsequently, the integrated model combining radiomics-based model and conventional model was established. The performance of three models was evaluated with discrimination, calibration, and clinical application.

RESULTS

The 65 keV radiomics-based scores of AP and VP had the optimal performance in distinguishing benign from malignant SPSNs (AUC_65keV-AP = 0.92, AUC_65keV-VP = 0.88). The diagnostic efficiency of radiomics-based model (AUC = 0.96) based on 65 keV images of AP and VP outperformed conventional model (AUC = 0.86) in the identification of SPSNs, and that of integrated model (AUC = 0.97) was slightly further improved. Evaluation of three models showed the potential for generalizability.

CONCLUSIONS

Among the 40-65 keV radiomics-based scores based on SDCT, 65 keV radiomics-based score had the optimal performance in distinguishing benign from malignant SPSNs. The integrated model combining radiomics-based model based on 65 keV images of AP and VP with Z_eff-AP was significantly superior to conventional model in the discrimination of SPSNs.

CLSSL-ResNet: Predicting malignancy of solitary pulmonary nodules from CT images by chimeric label with self-supervised learning

BACKGROUND

Pulmonary granulomatous nodules (GN) with spiculation or lobulation have a similar morphological appearance to solid lung adenocarcinoma (SADC) under computed tomography (CT). However, these two kinds of solid pulmonary nodules (SPN) have different malignancies and are sometimes misdiagnosed.

OBJECTIVE

This study aims to predict malignancies of SPNs by a deep learning model automatically.

METHODS

A chimeric label with self-supervised learning (CLSSL) is proposed to pre-train a ResNet-based network (CLSSL-ResNet) for distinguishing isolated atypical GN from SADC in CT images. The malignancy, rotation, and morphology labels are integrated into a chimeric label and utilized to pre-train a ResNet50. The pre-trained ResNet50 is then transferred and fine-tuned to predict the malignancy of SPN. Two image datasets of 428 subjects (Dataset1, 307; Dataset2, 121) from different hospitals are collected. Dataset1 is divided into training, validation, and test data by a ratio of 7:1:2 to develop the model. Dataset2 is utilized as an external validation dataset.

RESULTS

CLSSL-ResNet achieves an area under the ROC curve (AUC) of 0.944 and an accuracy (ACC) of 91.3%, which was much higher than that of the consensus of two experienced chest radiologists (77.3%). CLSSL-ResNet also outperforms other self-supervised learning models and many counterparts of other backbone networks. In Dataset2, AUC and ACC of CLSSL-ResNet are 0.923 and 89.3%, respectively. Additionally, the ablation experiment result indicates higher efficiency of the chimeric label.

CONCLUSION

CLSSL with morphology labels can increase the ability of feature representation by deep networks. As a non-invasive method, CLSSL-ResNet can distinguish GN from SADC via CT images and may support clinical diagnoses after further validation.

Epidemiological characteristics and quarantine assessment of imported international COVID-19 cases, March to December 2020, Chengdu, China

International flights have accelerated the global spread of Coronavirus Disease 2019 (COVID-19). Determination of the optimal quarantine period for international travelers is crucial to prevent the local spread caused by imported COVID-19 cases. We performed a retrospective epidemiological study using 491 imported COVID-19 cases in Chengdu, China, to describe the characteristic of the cases and estimate the time from arrival to confirmation for international travelers using nonparametric survival methods. Among the 491 imported COVID-19 cases, 194 (39.5%) were asymptomatic infections. The mean age was 35.6 years (SD = 12.1 years) and 83.3% were men. The majority (74.1%) were screened positive for SARS-CoV-2, conducted by Chengdu Customs District, the People's Republic of China. Asymptomatic cases were younger than presymptomatic or symptomatic cases (P < 0.01). The daily number of imported COVID-19 cases displayed jagged changes. 95% of COVID-19 cases were confirmed by PT-PCR within 14 days (95% CI 13-15) after arriving in Chengdu. A 14-day quarantine measure can ensure non-infection among international travelers with a 95% probability. Policymakers may consider an extension of the quarantine period to minimize the negative consequences of the COVID-19 confinement and prevent the international spread of COVID-19. Nevertheless, the government should consider the balance between COVID-19 and socioeconomic development, which may cause more serious social and health crises.

Analysis of the close contact management mode and epidemiological characteristics of COVID-19 in Chengdu, China

With the development of the novel coronavirus disease 2019 (COVID-19) epidemic and the increase in cases, as a potential source of infection, the risk of close contact has gradually increased. However, few studies have analyzed the tracking and management of cross-regional personnel. In this study, we hope to understand the effectiveness and feasibility of existing close contact management measures in Chengdu, so as to provide a reference for further prevention and control of the epidemic. The close contact management mode and epidemiological characteristics of 40,425 close contacts from January 22, 2020, to March 1, 2022, in Chengdu, China, were analyzed. The relationship with index cases was mainly co-passengers (57.58%) and relatives (7.20%), and the frequency of contact was mainly occasional contact (70.39%). A total of 400 (0.99%) close contacts were converted into cases, which were mainly found in the first and second nucleic acid tests (53.69%), and the contact mode was mainly by sharing transportation (63.82%). In terms of close contact management time, both the supposed ((11.93 ± 3.00) days vs. (11.92 ± 7.24) days) and actual ((13.74 ± 17.47) days vs. (12.60 ± 4.35) days) isolation times in Chengdu were longer than those of the outer cities (P < 0.001). For the local clustered epidemics in Chengdu, the relationship with indexed cases was mainly colleagues (12.70%). The tracing and management of close contacts is a two-way management measure that requires cooperation among departments. Enhancing existing monitoring and response capabilities can control the spread of the epidemic to a certain extent.

Deep multiple instance learning for predicting chemotherapy response in non-small cell lung cancer using pretreatment CT images

The individual prognosis of chemotherapy is quite different in non-small cell lung cancer (NSCLC). There is an urgent need to precisely predict and assess the treatment response. To develop a deep multiple-instance learning (DMIL) based model for predicting chemotherapy response in NSCLC in pretreatment CT images. Two datasets of NSCLC patients treated with chemotherapy as the first-line treatment were collected from two hospitals. Dataset 1 (163 response and 138 nonresponse) was used to train, validate, and test the DMIL model and dataset 2 (22 response and 20 nonresponse) was used as the external validation cohort. Five backbone networks in the feature extraction module and three pooling methods were compared. The DMIL with a pre-trained VGG16 backbone and an attention mechanism pooling performed the best, with an accuracy of 0.883 and area under the curve (AUC) of 0.982 on Dataset 1. While using max pooling and convolutional pooling, the AUC was 0.958 and 0.931, respectively. In Dataset 2, the best DMIL model produced an accuracy of 0.833 and AUC of 0.940. Deep learning models based on the MIL can predict chemotherapy response in NSCLC using pretreatment CT images and the pre-trained VGG16 with attention mechanism pooling yielded better predictions.

Hierarchical User Intention-Preference for Sequential Recommendation with Relation-Aware Heterogeneous Information Network Embedding

Existing recommender systems usually make recommendations by exploiting the binary relationship between users and items, and assume that users only have flat preferences for items. They ignore the users' intentions as an origin and driving force for users' performance. Cognitive science tells us that users' preference comes from an explicit intention. They first have an intention to possess a particular (type of) item(s) and then their preferences emerge when facing multiple available options. Most of the data used in recommender systems are composed of heterogeneous information contained in a complicated network's structure. Learning effective representations from these heterogeneous information networks (HINs) can help capture the user's intention and preferences, therefore, improving recommendation performance. We propose a hierarchical user's intention and preferences modeling for sequential recommendation based on relation-aware HIN embedding (HIP-RHINE). We first construct a multirelational semantic space of heterogeneous information networks to learn node embedding based on specific relations. We then model user's intention and preferences using hierarchical trees. Finally, we leverage the structured decision patterns to learn user's preferences and thereafter make recommendations. To demonstrate the effectiveness of our proposed model, we also report on the conducted experiments on three real data sets. The results demonstrated that our model achieves significant improvements in Recall and Mean Reciprocal Rank metrics compared with other baselines.

Humoral responses after inactivated COVID-19 vaccination in individuals with and without prior SARS-CoV-2 infection: A prospective cohort study

We evaluated and compared humoral immune responses after inactivated coronavirus disease 2019 (COVID-19) vaccination among naïve individuals, asymptomatically infected individuals, and recovered patients with varying severity. In this multicenter, prospective cohort study, blood samples from 666 participants were collected before and after 2 doses of inactivated COVID-19 vaccination. Among 392 severe acute respiratory syndrome coronavirus 2-naïve individuals, the seroconversion rate increased significantly from 51.8% (median antispike protein pan-immunoglobulins [S-Igs] titer: 0.8 U/ml) after the first dose to 96% (median S-Igs titer: 79.5 U/ml) after the second dose. Thirty-two percent of naïve individuals had detectable neutralizing antibodies (NAbs) against the original strain but all of them lost neutralizing activity against the Omicron variant. In 274 individuals with natural infection, humoral immunity was significantly improved after a single vaccine dose, with median S-Igs titers of 596.7, 1176, 1086.5, and 1828 U/ml for asymptomatic infections, mild cases, moderate cases, and severe/critical cases, respectively. NAb titers also improved significantly. However, the second dose did not substantially increase antibody levels. Although a booster dose is needed for those without infection, our findings indicate that recovered patients should receive only a single dose of the vaccine, regardless of the clinical severity, until there is sufficient evidence to confirm the benefits of a second dose.

Predicting chemotherapy response in non-small-cell lung cancer via computed tomography radiomic features: Peritumoral, intratumoral, or combined?

Purpose

This study aims to evaluate the ability of peritumoral, intratumoral, or combined computed tomography (CT) radiomic features to predict chemotherapy response in non-small cell lung cancer (NSCLC).

Methods

After excluding subjects with incomplete data or other types of treatments, 272 (Dataset 1) and 43 (Dataset 2, external validation) NSCLC patients who were only treated with chemotherapy as the first-line treatment were enrolled between 2015 and 2019. All patients were divided into response and nonresponse based on the response evaluation criteria in solid tumors, version 1.1. By using 3D slicer and morphological operations in python, the intra- and peritumoral regions of lung tumors were segmented from pre-treatment CT images (unenhanced) and confirmed by two experienced radiologists. Then radiomic features (the first order, texture, shape, et al.) were extracted from the above regions of interest. The models were trained and tested in Dataset 1 and further validated in Dataset 2. The performance of models was compared using the area under curve (AUC), confusion matrix, accuracy, precision, recall, and F1-score.

Results

The radiomic model using features from the peritumoral region of 0–3 mm outperformed that using features from 3–6, 6–9, 9–12 mm peritumoral region, and intratumoral region (AUC: 0.95 versus 0.87, 0.86, 0.85, and 0.88). By the fusion of features from 0–3 and 3–6 mm peritumoral regions, the logistic regression model achieved the best performance, with an AUC of 0.97. This model achieved an AUC of 0.85 in the external cohort. Moreover, among the 20 selected features, seven features differed significantly between the two groups (p < 0.05).

Conclusions

CT radiomic features from both the peri- and intratumoral regions can predict chemotherapy response in NSCLC using machine learning models. Combined features from two peritumoral regions yielded better predictions.

A fully automatic segmentation pipeline of pulmonary lobes before and after lobectomy from computed tomography images

BACKGROUND AND OBJECTIVE

Lobectomy is a curative treatment for localized lung cancer. The study aims to construct an automatic pipeline for segmenting pulmonary lobes before and after lobectomy from CT images.

MATERIALS AND METHODS

Six datasets (D1 to D6) of 865 CT scans were collected from two hospitals and public resources. Four nnU-Net-based segmentation models were trained. A lobectomy classification was proposed to automatically recognize the category of the input CT images: before lobectomy or one of five types after lobectomy. Finally, the lobe segmentation before and after lobectomy was realized by integrating the four models and lobectomy classification. The dice similarity coefficient (DSC), 95% Hausdorff distance (HD₉₅) and average symmetric surface distance (ASSD) were used to evaluate the segmentations.

RESULTS

The pre-operative model achieved an average DSC of 0.964, 0.929, 0.934, and 0.891 in the four datasets. In D1 and D2, the average HD₉₅ was 4.18 and 7.74 mm and the average ASSD was 0.86 and 1.32 mm, respectively. The lobectomy classification achieved an accuracy of 100%. After lobectomy, an average DSC of 0.973 and 0.936, an average HD₉₅ of 2.70 and 6.92 mm, an average ASSD of 0.57 and 1.78 mm were obtained in D1 and D2, respectively. The postoperative segmentation pipeline outperformed other counterparts and training strategies.

CONCLUSIONS

The proposed pipeline can automatically segment pulmonary lobes before and after lobectomy from CT images and be applied to manage patients with lung cancer after lobectomy.

Effects of carbazochrome sodium sulfonate combined with tranexamic acid on hemostasis and inflammation during perioperative period of total hip arthroplasty: A randomized controlled trial

BACKGROUND

The hemostatic effect of tranexamic acid (TXA) combined with carbazochrome sodium sulfonate (CSS) in total hip arthroplasty (THA) has not been determined. Therefore we performed a randomized study aiming to evaluate the effects of CSS combined with TXA on perioperative blood loss and inflammatory response of THA.

HYPOTHESIS

CSS combined with TXA can effectively reduce perioperative blood loss and immune response compared to TXA.

MATERIAL AND METHODS

This randomized placebo-controlled trial assigned 150 patients undergoing unilateral primary total hip arthroplasty who underwent direct anterior approach surgery to 3 groups: group A received TXA plus topical CSS; group B received TXA only; and group C received placebo. The main outcome was total blood loss. Secondary outcomes included reduction in hemoglobin concentration, coagulation parameters, inflammatory marker levels, perioperative visual analog scale (VAS) pain score, transfusion rates, postoperative hospital stay, and incidence of thromboembolic events.

RESULTS

Total blood loss in group A (668.84±230.95ml) was lower than in group B (940.96±359.22ml) and C (1166.52±342.85ml, p<0.05). We also found that compared with group B, postoperative hip pain, biomarker level of inflammation, visual analogue score (VAS) pain score in group A were significantly improved. The transfusion rate and unit of group A were significantly lower than group C (8 patients; 17.5 units), but there was no statistical difference between group A (no transfusion) and group B (2 patients; 4 units). No differences were observed in thromboembolic and other outcomes among the groups.

DISCUSSION

The combined application of topic CSS and TXA is more effective than TXA alone following THA in regard of reducing total blood loss. In addition, CSS combined with TXA is better than TXA alone in terms of improving postoperative hip pain and reducing the level of inflammatory factors.

LEVEL OF EVIDENCE

I; randomized controlled study.

Content-based image retrieval with a Convolutional Siamese Neural Network: Distinguishing lung cancer and tuberculosis in CT images

BACKGROUND

CT findings of lung cancer and tuberculosis are sometimes similar, potentially leading to misdiagnosis. This study aims to combine deep learning and content-based image retrieval (CBIR) to distinguish lung cancer (LC) from nodular/mass atypical tuberculosis (NMTB) in CT images.

METHODS

This study proposes CBIR with a convolutional Siamese neural network (CBIR-CSNN). First, the lesion patches are cropped out to compose LC and NMTB datasets and the pairs of two arbitrary patches form a patch-pair dataset. Second, this patch-pair dataset is utilized to train a CSNN. Third, a test patch is treated as a query. The distance between this query and 20 patches in both datasets is calculated using the trained CSNN. The patches closest to the query are used to give the final prediction by majority voting. One dataset of 719 patients is used to train and test the CBIR-CSNN. Another external dataset with 30 patients is employed to verify CBIR-CSNN.

RESULTS

The CBIR-CSNN achieves excellent performance at the patch level with an mAP (Mean Average Precision) of 0.953, an accuracy of 0.947, and an area under the curve (AUC) of 0.970. At the patient level, the CBIR-CSNN correctly predicted all labels. In the external dataset, the CBIR-CSNN has an accuracy of 0.802 and AUC of 0.858 at the patch level, and 0.833 and 0.902 at the patient level.

CONCLUSIONS

This CBIR-CSNN can accurately and automatically distinguish LC from NMTB using CT images. CBIR-CSNN has excellent representation capability, compatibility with few-shot learning, and visual explainability.

[Analysis on the imported Coronavirus Disease 2019 related cluster epidemic in rural areas of Chengdu]

An epidemiological investigation was carried out on a local cluster of outbreak caused by imported cases of Coronavirus Disease 2019 (COVID-19) in rural areas of Chengdu in December 2020, to find out the source of infection and the chain of transmission. According to Prevention and Control Protocol for COVID-19 (Version 7), field epidemiological investigation was adopted, combined with big data technology, video image investigation, gene sequencing and other methods to carry out investigation into COVID-19 cases and infections source tracing, analyze the epidemiological association, and map the chain of transmission. From December 7 to 17, 2020, 13 local COVID-19 confirmed cases and 1 asymptomatic case were diagnosed in Chengdu, of which 12 cases (85.71%) had a history of residence and activity in the village courtyard of Taiping (TP), Pidu (P) District, Chengdu. From November 8, 2020 to November 28, 2020, a group of inbound people form Nepal were transferred to the designated entry personnel quarantine hotel of P District which was adjacent to the TP village. During quarantine, there were 5 cases who tested positive for COVID-19. Through gene sequencing alignment, genes of local cases and Nepalese imported cases from the same period are homologous, all belong to the lineage of L2.2.3 (B.1.36 according to Pangolin lineage typing method). According to the results of field epidemiological investigation and gene sequencing analysis, the index case was most likely infected by contact with household waste of quarantine site. Under the situation of normalization prevention and control of COVID-19, sentinel monitoring of fever clinics in primary medical institutions is the key to early detection of the epidemic. The multi-department joint epidemiological investigation and the application of gene technology are the core links of the investigation and traceability of modern infectious diseases. The allocation of public health resources in rural areas needs to be strengthened. We need to improve the capacity for early surveillance and early warning of the epidemic in rural areas.

A survey of a COVID-19 cluster of charter flight importation

OBJECTIVES

Although a number of cases of importation with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection have been reported, there are still no data available concerning the characteristics in the coronavirus disease 2019 (COVID-19) cluster of charter flight importation. Here, we provide an analysis of COVID-19 cases and their close contacts who worked for the same company on a project in Karbala, Iraq, and returned back to Chengdu, China, by a charter flight.

METHODS

The data of imported COVID-19 cases and their close contacts were obtained from National Notifiable Disease Report System of Chinese Center for Disease Control and Prevention and field epidemiological investigation reports by Centers for Disease Control and Prevention (CDCs) in Chengdu. The information of general characteristics and laboratory findings of this cluster were collected and summarized.

RESULTS

One hundred and six (66.67%) of 159 charter flight passengers tested positive for COVID-19 before entry. Through treatment, all 159 people tested negative and meet the requirements of taking flights bound for China before boarding. However, there has been still 36 (22.64%) of them tested positive after entry. The median time from entry to confirmation was 1.0 day (Interquartile Range (IQR): 0-4.3). The Cycle threshold value (Ct value) of 36 patients' positive samples are all above 30 and most values are above 35.

CONCLUSIONS

In conclusion, there is still a risk that a number of COVID-19 cases can be imported through charter flight. However, the infectivity of confirmed patients of the charter flight was considered to be low.

RNA interference of Argonaute-1 delays ovarian development in the oriental fruit fly, Bactrocera dorsalis (Hendel)

BACKGROUND

With the development of rapid resistance, new modes of action for pesticides are needed for insect control, such as RNAi-based biopesticides targeting essential genes. To explore the function of Argonaute-1 (Ago-1) and potential miRNAs in ovarian development of Bactrocera dorsalis, an important agricultural pest, and to develop a novel control strategy for the pest, BdAgo-1 was first identified in B. dorsalis.

RESULTS

Spatiotemporal expression analysis indicated that BdAgo-1 had a relatively high transcriptional level in the ovarian tissues of adult female B. dorsalis during the sexual maturation period. RNA interference (RNAi) experiment showed that BdAgo-1 knockdown significantly decreased the expression levels of ovarian development-related genes and delayed ovarian development. Although RNAi-mediated silencing of Ago-1 led to a reduced ovary surface area, a subsequent oviposition assay revealed that the influence was minimal over a longer time period. Small RNA libraries were constructed and sequenced from different ovarian developmental stages of B. dorsalis adults. Among 161 identified miRNAs, 84 miRNAs were differentially expressed during the three developmental stages of the B. dorsalis ovary. BdAgo-1 silencing caused significant down-regulation of seven differentially expressed miRNAs (DEMs) showing relatively high expression levels (>1000 TPM (Transcripts per kilobase of exon model per million mapped reads)). The expression patterns of these seven core DEMs and their putative target genes were analyzed in the ovaries of B. dorsalis.

CONCLUSION

The results indicate that Ago-1 and Ago-1-dependent miRNAs are indispensable for normal ovarian development in B. dorsalis and help identify miRNA targets useful for control of this pest.

[Influence of SARS-CoV-2 vaccination on the epidemiological and clinical characteristics of imported COVID-19 cases in Chengdu]

Objective: To analyze the epidemiological and clinical characteristics of imported COVID-19 cases after SARS-CoV-2 vaccination and to provide evidence for the prevention and control of COVID-19. Methods: The imported COVID-19 cases in Chengdu as of April 15, 2021 were divided into the vaccinated group and unvaccinated group according to the history of SARS-CoV-2 vaccination. The epidemiological and clinical data of the cases were collected retrospectively, and the differences in epidemiological and clinical characteristics of the two groups were compared. Laboratory tests consisted of nucleic acid test, clinical index test, serum antibody test and lymphocyte test. Software WPS2019 was used for data management and software R 4.0.3 was used for statistical analysis. Results: A total of 75 COVID-19 cases were included in the analysis, in which 20 had received SARS-CoV-2 vaccination and only 4 with clinical symptoms, 55 patients did not receive SARS-CoV-2 vaccination, and 16 had clinical symptoms. In vaccinated group, the first injection time of vaccination ranged from July to November 2020, and 10 cases received two doses of vaccine simultaneously and 10 cases received two doses of vaccine at intervals of 14-57 days. The intervals between the completion of vaccination and the onset ranged from 87 days to 224 days. The differences in classification and clinical type between the two groups were significant. Significant differences were observed in case classification and clinical type between vaccinated group and unvaccinated group (P<0.05). The vaccinated group had a relatively high proportion of asymptomatic infections (40.00%, 8/20), while mild infections were mainly observed in the unvaccinated group(76.36%,42/55). The differences in Ct values (ORF1ab gene and N gene) at the diagnosis were not significant between vaccinated group and unvaccinated group (P>0.05), similar results were also observed in lymphocyte subtypes, procalcitonin and C-reactive protein level comparisons. Serum amyloid A level was higher in unvaccinated group than in vaccinated group (P<0.05). However, the SARS-CoV-2 related serum antibody of IgM, IgG and total antibody levels were significantly higher in vaccinated group (P<0.05). Conclusions: Risk of infection still exists with SARS-CoV-2 after vaccination, which can facilitate the production of specific serum antibody of IgM and IgG when people are exposed to the virus. It has a certain protective effect on SARS-CoV-2 infected persons. Vaccination can reduce the clinical symptoms and mitigate disease severity.

Predictive Radiomic Models for the Chemotherapy Response in Non-Small-Cell Lung Cancer based on Computerized-Tomography Images

The heterogeneity and complexity of non-small cell lung cancer (NSCLC) tumors mean that NSCLC patients at the same stage can have different chemotherapy prognoses. Accurate predictive models could recognize NSCLC patients likely to respond to chemotherapy so that they can be given personalized and effective treatment. We propose to identify predictive imaging biomarkers from pre-treatment CT images and construct a radiomic model that can predict the chemotherapy response in NSCLC. This single-center cohort study included 280 NSCLC patients who received first-line chemotherapy treatment. Non-contrast CT images were taken before and after the chemotherapy, and clinical information were collected. Based on the Response Evaluation Criteria in Solid Tumors and clinical criteria, the responses were classified into two categories: response (n = 145) and progression (n = 135), then all data were divided into two cohorts: training cohort (224 patients) and independent test cohort (56 patients). In total, 1629 features characterizing the tumor phenotype were extracted from a cube containing the tumor lesion cropped from the pre-chemotherapy CT images. After dimensionality reduction, predictive models of the chemotherapy response of NSCLC with different feature selection methods and different machine-learning classifiers (support vector machine, random forest, and logistic regression) were constructed. For the independent test cohort, the predictive model based on a random-forest classifier with 20 radiomic features achieved the best performance, with an accuracy of 85.7% and an area under the receiver operating characteristic curve of 0.941 (95% confidence interval, 0.898–0.982). Of the 20 selected features, four were first-order statistics of image intensity and the others were texture features. For nine features, there were significant differences between the response and progression groups (p < 0.001). In the response group, three features, indicating heterogeneity, were overrepresented and one feature indicating homogeneity was underrepresented. The proposed radiomic model with pre-chemotherapy CT features can predict the chemotherapy response of patients with non-small cell lung cancer. This radiomic model can help to stratify patients with NSCLC, thereby offering the prospect of better treatment.

Identification of Proteomic Signatures in Chronic Obstructive Pulmonary Disease Emphysematous Phenotype

Chronic obstructive pulmonary disease (COPD) is a highly heterogeneous disease. Emphysematous phenotype is the most common and critical phenotype, which is characterized by progressive lung destruction and poor prognosis. However, the underlying mechanism of this structural damage has not been completely elucidated. A total of 12 patients with COPD emphysematous phenotype (COPD-E) and nine patients with COPD non-emphysematous phenotype (COPD-NE) were enrolled to determine differences in differential abundant protein (DAP) expression between both groups. Quantitative tandem mass tag–based proteomics was performed on lung tissue samples of all patients. A total of 29 and 15 lung tissue samples from patients in COPD-E and COPD-NE groups, respectively, were used as the validation cohort to verify the proteomic analysis results using western blotting. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted for DAPs. A total of 4,343 proteins were identified, of which 25 were upregulated and 11 were downregulated in the COPD-E group. GO and KEGG analyses showed that wound repair and retinol metabolism–related pathways play an essential role in the molecular mechanism of COPD emphysematous phenotype. Three proteins, namely, KRT17, DHRS9, and FMO3, were selected for validation. While KRT17 and DHRS9 were highly expressed in the lung tissue samples of the COPD-E group, FMO3 expression was not significantly different between both groups. In conclusion, KRT17 and DHRS9 are highly expressed in the lung tissue of patients with COPD emphysematous phenotype. Therefore, these proteins might involve in wound healing and retinol metabolism in patients with emphysematous phenotype and can be used as phenotype-specific markers.

Enhancing remediation of PAH-contaminated soil through coupling electrical resistance heating using Na2S2O8

Soil polycyclic aromatic hydrocarbons (PAHs) contamination caused by factory relocations is a serious environmental issue across the world. Electrical resistance heating (ERH) and chemical oxidation are two promising in-situ methods for treating volatile and semi-volatile organic pollutants in contaminated soil. Coupling of ERH and chemical oxidation technologies to improve the remediation efficiency for PAH-contaminated soil was estimated in this study. PAH removal ratio in contaminated soils using ERH treatment were significantly negatively correlated with the boiling point of the pollutants (P = 0.002), and 21.63% (DBA high boiling point) to 71.53% (Nap low boiling point) of PAHs in the contaminated soil were removed in 120 min. With oxidant Na₂S₂O₈ coupling, the removal ratio were increased as more oxidant was added. For one Phe, 35.90% was removed by ERH treatment and increased to 52.90% and 79.42% when 0.05 or 2.5 mmol/g oxidant was added, respectively. PAHs with higher boiling points had more obvious removal ratio, such as Bap, which increased from 23.50% to 85.47% when coupling ERH with Na₂S₂O₈, and Phe which increased from 35.90% to 79.42%. Relationships between boiling points and PAH removal ratio changed with coupled oxidants, indicating a change of mechanism from volatilization to coupling effects of volatilization and oxidation with the introduction of Na₂S₂O₈. A dynamic experiment showed that Na₂S₂O₈ can accelerate 45.50% of the treatment process. The results of this research demonstrated a novel, cost-effective coupling approach for remediating soil contaminated by organic pollutants.

Multiple-camera defocus imaging of ultracold atomic gases

In cold atom experiments, each image of light refracted and absorbed by an atomic ensemble carries a remarkable amount of information. Numerous imaging techniques including absorption, fluorescence, and phase-contrast are commonly used. Other techniques such as off-resonance defocused imaging (ORDI, [1-4]), where an in-focus image is deconvolved from a defocused image, have been demonstrated but find only niche applications. The ORDI inversion process introduces systematic artifacts because it relies on regularization to account for missing information at some spatial frequencies. In the present work, we extend ORDI to use multiple cameras simultaneously at degrees of defocus, eliminating the need for regularization and its attendant artifacts. We demonstrate this technique by imaging Bose-Einstein condensates, and show that the statistical uncertainties in the measured column density using the multiple-camera off-resonance defocused (McORD) imaging method are competitive with absorption imaging near resonance and phase contrast imaging far from resonance. Experimentally, the McORD method may be incorporated into existing set-ups with minimal additional equipment.

Analysis of transient response of the human foot based on the finite element method

BACKGROUND

The foot is an important part of the human body. Its functions are mainly walking and load-bearing. It also keeps the human body stable and absorbs ground vibrations to protect important human organs.

OBJECTIVE

Many researchers use finite element methods to study the biomechanics of the foot. However, current studies on the finite element of the foot are based on the stress and displacement response analysis of the foot under static or quasi-static conditions, ignoring the movement process of the foot and the impact of vibration. Moreover, the joint application of energy method and finite element analysis in foot biomechanics is rarely reported.

METHODS

In this paper, to obtain the foot energy transfer process, the transient response of the foot under neutral position is analyzed based on the energy method.

RESULTS

The results show that: (1) In this model, the energy analysis follows the conservation of energy, which indicates that the transient response analysis has obtained a reasonable response. (2) When the foot touches the ground, the strain energy of the calcaneus, second metatarsal and third metatarsal is relatively large, which is consistent with the main stress concentration area of the plantar. (3) The gravity of the human body is mainly transmitted through the talus to the calcaneus, while the effect of transmittal through the scaphoid to the cuneiform bone and metatarsal is weak.

CONCLUSION

This study can not only more clearly and intuitively reflect the energy transfer and source of various skeletal foreheads in the foot, but also provide a new research idea for the study of foot biomechanics.

Surface charge engineering of Thermomyces lanuginosus lipase improves enzymatic activity and biodiesel synthesis

OBJECTIVES

This study was aimed at engineering charged residues on the surface of Thermomyces lanuginosus lipase (TLL) to obtain TLL variant with elevated performance for industrial applications.

RESULTS

Site-directed mutagenesis of eight charged amino acids on the TLL surface were conducted and substitutions on the negatively charged residues D111, D158, D165, and E239 were identified with elevated specific activities and biodiesel yields. Synergistic effect was not discovered in the double mutants, D111E/D165E and D165E/E239R, when compared with the corresponding single mutants. One TLL mutant, D165E, was identified with increased specific activity (456.60 U/mg), catalytic efficiency (k_cat/K_m: 44.14 s^-1 mM^-1), the highest biodiesel conversion yield (93.56%), and comparable thermostability with that of the TLL.

CONCLUSIONS

Our study highlighted the importance of surface charge engineering in improving TLL activity and biodiesel production, and the resulting TLL mutant, D165E, is a promising candidate for biodiesel industry.

Prospective evaluation of dietary and lifestyle pattern indices with risk of colorectal cancer in a cohort of younger women

BACKGROUND

Although colorectal cancer (CRC) incidence in the USA is declining overall, its incidence is increasing among those younger than 50 years of age. The reasons underlying the increasing trend are largely unknown, although behavioral changes, such as unhealthy diet and lifestyle factors, may be partially responsible.

DESIGN

A prospective cohort study included 94 217 women aged 26-45 years at baseline. Validated anthropometric measures and lifestyle information were self-reported biennially. Exposures were four recommendation-based dietary indices-the prime diet quality score and three plant-based dietary indices; and two mechanism-based indices-the empirical dietary and lifestyle index for hyperinsulinemia (EDIH and ELIH). We calculated hazard ratios (HRs) and 95% confidence intervals (CIs) for overall CRC and for early-onset (before age 50) and after age 50 CRC separately.

RESULTS

We documented 332 cases of CRC during 24 years of follow-up (2 113 655 person-years), with an average age of 52 ± 7 years at diagnosis. Hyperinsulinemic dietary and lifestyle patterns were associated with a higher risk of CRC. Multivariable-adjusted HRs (95% CIs) comparing participants in the highest versus lowest quartile were: 1.67 for EDIH (95% CI: 1.15-2.44, P-trend = 0.01) and 1.51 for ELIH (95% CI: 1.10-2.08, P-trend = 0.01). Moreover, per 75% increment in rank, ELIH appeared to be a stronger risk factor for early-onset CRC (HR = 1.86, 95% CI: 1.12-3.07) than after age 50 CRC (HR = 1.20, 95% CI: 0.83-1.73, P-heterogeneity = 0.16). The four recommendation-based indices were not significantly associated with overall, early-onset, or after age 50 CRC risk (per 75% increment in rank, HRs ranged from 0.75 to 1.28).

CONCLUSION

Dietary and lifestyle patterns contributing to hyperinsulinemia were associated with greater CRC risk in younger women. Moreover, the hyperinsulinemic lifestyle showed a suggestively stronger positive association with early-onset CRC risk, compared with after age 50 CRC. Our findings suggest that dietary and lifestyle interventions to reduce insulinemic potential may be effective for CRC prevention among younger women.

Superimposing hip extension on knee flexion evokes higher activation in biceps femoris than knee flexion alone

Hamstring muscle function during knee flexion has been linked to hamstring injury and performance. However, it is unclear whether knee flexion alone (KF) requires similar hamstring electromyography (EMG) activity pattern to simultaneous hip extension and knee flexion (HE-KF), a combination that occurs in the late swing phase of sprinting. This study examined whether HE-KF maximal voluntary isometric contraction (MVIC) evokes higher (EMG) activity in biceps femoris long head (BFlh) and semitendinosus (ST) than KF alone. Effects of shank rotation angles were also tested. Twenty-one males performed the above-mentioned MVICs while EMG activity was measured along ST and BFlh. Conditions were compared using a one-way mixed functional ANOVA model under a fully Bayesian framework. Higher EMG activity was found in HE-KF in all shank rotation positions than in KF in the middle region of BFlh (highest in the 9th channel, by 0.022 mV [95%CrI 0.014 to 0.030] in neutral shank position). For ST, this was only observed in the neutral shank position and in the most proximal channel (by 0.013 mV [95%CrI 0.001 to 0.025]). We observed muscle- and region-specific responses to HE-KF. Future studies should examine whether hamstring activation in this task is related to injury risk and sprint performance.

The application of dual-layer spectral detector computed tomography in solitary pulmonary nodule identification

Background

Differentiating between malignant solitary pulmonary nodules (SPNs) and other lung diseases remains a substantial challenge. The latest generation of dual-energy computed tomography (CT), which realizes dual-energy technology at the detector level, has clinical potential for distinguishing lung cancer from other benign SPNs. This study aimed to evaluate the performance of dual-layer spectral detector CT (SDCT) for the differentiation of SPNs.

Methods

Spectral images of 135 SPNs confirmed by pathology were retrospectively analyzed in both the arterial phase (AP) and the venous phase (VP). Patients were classified into two groups [the malignant group (n=93) and the benign group (n=42)], with the malignant group further divided into small cell lung cancer (SCLC, n=30) and non-small cell lung cancer (NSCLC, n=63) subtypes. The slope of the spectral Hounsfield Unit (HU) curve (λ_HU), normalized iodine concentration (NIC), CT values of 40 keV monochromatic images (CT_40keV), and normalized arterial enhancement fraction (NAEF) in contrast-enhanced images were calculated and compared between the benign and malignant groups, as well as between the SCLC and NSCLC subgroups. ROC curve analysis was performed to assess the diagnostic performance of the above parameters. Seventy cases were randomly selected and independently measured by two radiologists, and intraclass correlation coefficient (ICC) and Bland-Altman analyses were performed to calculate the reliability of the measurements.

Results

Except for NAEF (P=0.23), the values of the parameters were higher in the malignant group than in the benign group (all P<0.05). NIC, λ_HU, and CT_40keV performed better in the VP (NIC_VP, λ_VPHU, and CT_VP40keV) (P<0.001), with an area under the ROC curve (AUC) of 0.93, 0.89, and 0.89 respectively. With respective cutoffs of 0.31, 1.83, and 141.00 HU, the accuracy of NIC_VP, λ_VPHU, and CT_VP40keV was 91.11%, 85.19%, and 88.15%, respectively. In the subgroup differentiating NSCLC and SCLC, the diagnostic performances of NIC_AP (AUC =0.89) were greater than other parameters. NIC_AP had an accuracy of 86.02% when the cutoff was 0.14. ICC and Bland-Altman analyses indicated that the measurement of SDCT has great reproducibility.

Conclusions

Quantitative measures from SDCT can help to differentiate benign from malignant SPNs and may help with the further subclassification of malignant cancer into SCLC and NSCLC.

Life-threatening complications after microvascular decompression procedure: Lessons from a consecutive series of 596 patients

The microvascular decompression procedure (MVD) is widely utilized on patients with neurovascular compression syndromes, such as trigeminal neuralgia, hemifacial spasm and glossopharyngeal neuralgia, which have failed medical therapy. However, surgical complications are an ongoing problem. We retrospectively reviewed a total of 596 patients undergoing MVD in the Affiliated Hospital of Qingdao University from January 2008 to December 2018. Furthermore, we discussed the cases with life-threatening complications to determine the potential causes, aiming to achieve the goal of safer microvascular decompression. There were seven cases with life-threatening complications. Of those complications, one was cerebellar infarction with acute hydrocephalus, one was infarction of the cerebellum and the brain stem with acute hydrocephalus and serious intracranial infection, two were cerebellar haematoma, one was multiple haemorrhage with acute hydrocephalus, one was supratentorial subdural haematoma, and one was cerebellar swelling with acute hydrocephalus. After therapy, one patient died, one was in a persistent vegetative state, and five were discharged from the hospital upon recovery. In brief, MVD is a safe operation, and life-threatening complications accompanying MVD are rare, but require attention. The causes of some life-threatening complications are still not completely clear. Surgeons should continuously improve surgical techniques and perioperative care to reduce potential risks.

Clinicopathological and Prognostic Significance of Immunoscore and PD-L1 in Intrahepatic Cholangiocarcinoma

Background

An increasing amount of evidence reveals that immunosuppression is a major issue in cancer progression. The association of immunoscore (IS) and its impact on clinical outcome have been studied in many tumor types, but its significance in intrahepatic cholangiocarcinoma (ICC) is poorly known.

Methods

By immunohistochemistry, CD3 and CD8 expressions were assessed in tissue samples of 50 cases of postoperative ICC. The IS was determined by analyzing CD3+ and CD8+ expression data in different areas (intratumor and invasion margins). The relationship between IS and clinicopathological characteristics, including the overall survival (OS) and recurrence-free survival (RFS), was analyzed. In addition, PD-L1, a major regulator of immune escape, was also assessed in tumor cells by immunohistochemistry.

Results

IS was related to histological differentiation (P=0.026), the presence of lymphoid metastasis (P=0.034), and TNM clinical stages (P = 0.031) of ICC. High IS was significantly associated with better RFS (P=0.033) and OS (P=0.014). IS was an independent prognostic factor for better OS in multivariate analysis. PD-L1 expression was closely related to tumor vascular invasion (P=0.044). Although there was no association between PD-L1 expression and IS, high PD-L1 expression in tumor cells indicated poor RFS (P=0.017) and OS (P=0.004) in ICC.

Conclusion

The IS and PD-L1 may be used as a complement to the TNM system for predicting the prognosis of patients with ICC.

Comparison of Postoperative Outcomes Between Traditional Longitudinal Incision and Bikini Incision in Total Hip Arthroplasty via Direct Anterior Approach: A Randomized Controlled Trial

BACKGROUND

The purpose of this study is to compare a traditional longitudinal incision to an oblique "bikini" incision during total hip arthroplasty (THA) via direct anterior approach (DAA), in terms of the aesthetic appearance of the scar, postoperative functional recovery, and complications.

METHODS

This study is a single-surgeon experience in the Chinese population. Patients who came to our institute needing a THA via DAA were enrolled in our randomized controlled trial and randomly allocated to undergo traditional longitudinal incision (control) or bikini incision. Primary outcomes were measured using the scar cosmesis assessment and rating scale, the visual analog scale for pain, Oxford hip score, and University of California Los Angeles activity-level rating. Secondary outcomes were postoperative serum markers of muscle damage, inflammation, hemoglobin drop, and implant stability. The occurrence of postoperative complications, such as nerve and wound healing, was also recorded.

RESULTS

There were no differences in demographic or clinical characteristics before surgery. A greater proportion of patients in the bikini group were satisfied with the appearance of their scar, giving significantly better scar cosmesis assessment and rating scores. There was no difference in postoperative functional recovery, levels of serum markers, or positioning of the implant components. Incision type had no effect on duration of hospitalization. The incidence of complications did not differ significantly between groups.

CONCLUSION

The bikini incision can improve patients' subjective satisfaction with scar aesthetics after THA via DAA and does not detract from a quick functional recovery. Studies with larger sample sizes should be conducted to further investigate associated complications.

THE CLINICAL TRIAL REGISTRATION NUMBER

ChiCTR1900022870.

Tamoxifen attenuates reactive astrocyte-induced brain metastasis and drug resistance through the IL-6/STAT3 signaling pathway

Brain metastasis affects approximately 20%-30% of patients with triple-negative breast cancers (TNBCs). Even small metastatic lesions in the brain can trigger severe neurological impairments and result in extremely short survival time. Recently, active astrocytes were reported to be associated with brain metastases. However, how activated astrocytes regulate the behaviors of disseminated breast cancer cells in the brain remains unknown. In this study, human primary astrocytes were stimulated with IL-1β to form active astrocytes to study the cross-talk between stromal cells (astrocytes) and TNBC cells in brain metastases. Our results showed that active astrocytes significantly increase the malignancy of TNBC cells and prevent them from undergoing apoptosis caused by doxorubicin. We also found that the high level of IL-6 secreted by activated astrocytes was responsible for the drug resistance of breast cancer, which could be abolished by treatment of astrocytes with tamoxifen (TAM). The blockage of active astrocyte-derived IL-6 by a neutralizing antibody resulted in the attenuation of drug resistance, consequently enhancing the sensitivity of breast cancer cells to doxorubicin. Furthermore, the possible involved TAM-modulated drug resistance mechanism may be associated with a decrease in IL-6 expression in astrocytes and the downregulation of MAPK and JAK2/STAT3 signaling in cancer cells. Our data suggested that TAMs might reduce drug resistance through the IL-6/JAK2/STAT3 signaling pathway, providing a possible therapy to treat brain metastasis in TNBCs, as estrogen receptor inhibitors (TAMs, etc.) can cross the blood-brain barrier.