Comparison of uncut Roux-en-Y anastomosis and Billroth-II with Braun anastomosis after distal gastrectomy.

Background: This study aimed to compare the clinical outcomes and patient benefits of uncut Roux-en-Y (URY) anastomosis and Billroth-II with Braun (BB) anastomosis after distal gastrectomy. Methods: We retrospectively reviewed the data of patients who underwent URY or BB anastomosis after distal gastrectomy between March 2015 and December 2017. Clinical characteristics, survival data, postoperative recovery data, and long-term outcomes were recorded and compared between the two groups. Results: A total of 231 patients were included, with 167 in the URY group and 64 in the BB group. Kaplan-Meier curves for overall survival showed no differences after propensity score matching (p = 0.488). Long-term postoperative quality of life evaluation also showed no significant differences. Compared to the BB group, patients in the URY group had a significantly shorter time to start a liquid diet after propensity score matching (67.6 h vs. 46.5 h, p = 0.003), and a lower occurrence of bile reflux on follow-up gastroscopy (p < 0.001). Conclusion: The URY anastomosis appears to be a feasible method for digestive tract reconstruction after distal gastrectomy, resulting in less bile reflux and better postoperative recovery. However, there is no significant difference between URY and BB anastomosis in terms of overall survival and long-term quality of life.

Genomic characterization of peritoneal lavage cytology-positive gastric cancer.

Objective: Positive peritoneal lavege cytology (CY1) gastric cancer is featured by dismal prognosis, with high risks of peritoneal metastasis. However, there is a lack of evidence on pathogenic mechanism and signature of CY1 and there is a continuous debate on CY1 therapy. Therefore, exploring the mechanism of CY1 is crucial for treatment strategies and targets for CY1 gastric cancer. Methods: In order to figure out specific driver genes and marker genes of CY1 gastric cancer, and ultimately offer clues for potential marker and risk assessment of CY1, 17 cytology-positive gastric cancer patients and 31 matched cytology-negative gastric cancer patients were enrolled in this study. The enrollment criteria were based on the results of diagnostic laparoscopy staging and cytology inspection of exfoliated cells. Whole exome sequencing was then performed on tumor samples to evaluate genomic characterization of cytology-positive gastric cancer. Results: Least absolute shrinkage and selection operator (LASSO) algorithm identified 43 cytology-positive marker genes, while MutSigCV identified 42 cytology-positive specific driver genes. CD3G and CDKL2 were both driver and marker genes of CY1. Regarding mutational signatures, driver gene mutation and tumor subclone architecture, no significant differences were observed between CY1 and negative peritoneal lavege cytology (CY0). Conclusions: There might not be distinct differences between CY1 and CY0, and CY1 might represent the progression of CY0 gastric cancer rather than constituting an independent subtype. This genomic analysis will thus provide key molecular insights into CY1, which may have a direct effect on treatment recommendations for CY1 and CY0 patients, and provides opportunities for genome-guided clinical trials and drug development.

Altered metabolism in right basal ganglia associated with asymptomatic neurocognitive impairment in HIV-infected individuals.

Background: Only few studies have focused on the metabolite differences between asymptomatic neurocognitive impairment (ANI) and cognitively normal people living with HIV (PLWH). The current study aims to examine whether brain metabolisms in basal ganglia (BG) by magnetic resonance spectroscopy (MRS) were potential to discriminate ANI from cognitively normal PLWH. Methods: According to neuropsychological (NP) test, 80 PLWH (37.4 ± 10.2 years) were divided into ANI group (HIV-ANI, n = 31) and NP normal group (HIV-normal, n = 49). Brain metabolisms by MRS from right BG were compared between groups, including N-acetylaspartate and N-acetyl aspartylglutamate (tNAA), creatine and phosphocreatine (tCr), and choline-containing compounds (tCho). A total value of three metabolites were introduced. All brain metabolisms were evaluated as its percentage of total. Furthermore, correlations between MRS and NP and clinical measures were evaluated. A logistic regression model was applied, and the AUC values for the model and the continuous factors were compared using receiver operating curve (ROC) analysis. Results: Compared to HIV-normal group, tNAA/total was lower and tCr/total was higher in the HIV-ANI group (P < 0.05). Both tNAA/total and tCr/total values were correlated with NP score (P < 0.05), especially in verbal fluency, speed of information processing, learning, and recall (P < 0.05). The logistic model included BG-tCr/total, current CD4 and infection years of PLWH. The AUC value for the BG-tCr/total was 0.696 and was not significantly lower than that for logistic model (P < 0.01). Conclusion: The altered brain metabolites in the right BG were found in the ANI group compared to PLWH with normal cognition, and further associated with NP deficits. The current findings indicated that brain metabolites assessed by MRS has the potential to discriminate ANI from cognitively normal PLWH.

Short-term outcomes and long-term quality of life of reconstruction methods after proximal gastrectomy: a systematic review and meta-analysis.

BACKGROUND: The optimal reconstruction method after proximal gastrectomy remains unclear. This systematic review and meta-analysis aimed to compare the short-term outcomes and long-term quality of life of various reconstruction methods. METHODS: PubMed, Embase, Web of Science and Cochrane Library were searched to identify comparative studies concerning the reconstruction methods after proximal gastrectomy. The reconstruction methods were classified into six groups: double tract reconstruction (DTR), esophagogastrostomy (EG), gastric tube reconstruction (GT), jejunal interposition (JI), jejunal pouch interposition (JPI) and double flap technique (DFT). Esophagogastric anastomosis group (EG group) included EG, GT and DFT, while esophagojejunal anastomosis group (EJ group) included DTR, JI and JPI. RESULTS: A total of 27 studies with 2410 patients were included in this meta-analysis. The pooled results indicated that the incidences of reflux esophagitis of DTR, EG, GT, JI, JPI and DFT were 7.6%, 27.3%, 4.5%, 7.1%, 14.0%, and 9.1%, respectively. The EG group had more reflux esophagitis (OR = 3.68, 95%CI 2.44-5.57, P < 0.00001) and anastomotic stricture (OR = 1.58, 95%CI 1.02-2.45, P = 0.04) than the EJ group. But the EG group showed shorter operation time (MD=-56.34, 95%CI -76.75- -35.94, P < 0.00001), lesser intraoperative blood loss (MD=-126.52, 95%CI -187.91- -65.12, P < 0.0001) and shorter postoperative hospital stay (MD=-2.07, 95%CI -3.66- -0.48, P = 0.01). Meanwhile, the EG group had fewer postoperative complications (OR = 0.68, 95%CI 0.51-0.90, P = 0.006) and lesser weight loss (MD=-1.25, 95%CI -2.11- -0.39, P = 0.004). For specific reconstruction methods, there were lesser reflux esophagitis (OR = 0.10, 95%CI 0.06-0.18, P < 0.00001) and anastomotic stricture (OR = 0.14, 95%CI 0.06-0.33, P < 0.00001) in DTR than the esophagogastrostomy. DTR and esophagogastrostomy showed no significant difference in anastomotic leakage (OR = 1.01, 95%CI 0.34-3.01, P = 0.98). CONCLUSION: Esophagojejunal anastomosis after proximal gastrectomy can reduce the incidences of reflux esophagitis and anastomotic stricture, while esophagogastric anastomosis has advantages in technical simplicity and long-term weight status. Double tract reconstruction is a safe technique with excellent anti-reflux effectiveness and favorable quality of life. REGISTRATION: This meta-analysis was registered on the PROSPERO (CRD42022381357).

Chinese expert consensus on imaging diagnosis of drug-resistant pulmonary tuberculosis.

Tuberculosis (TB) remains one of the major infectious diseases in the world with a high incidence rate. Drug-resistant tuberculosis (DR-TB) is a key and difficult challenge in the prevention and treatment of TB. Early, rapid, and accurate diagnosis of DR-TB is essential for selecting appropriate and personalized treatment and is an important means of reducing disease transmission and mortality. In recent years, imaging diagnosis of DR-TB has developed rapidly, but there is a lack of consistent understanding. To this end, the Infectious Disease Imaging Group, Infectious Disease Branch, Chinese Research Hospital Association; Infectious Diseases Group of Chinese Medical Association of Radiology; Digital Health Committee of China Association for the Promotion of Science and Technology Industrialization, and other organizations, formed a group of TB experts across China. The conglomerate then considered the Chinese and international diagnosis and treatment status of DR-TB, China's clinical practice, and evidence-based medicine on the methodological requirements of guidelines and standards. After repeated discussion, the expert consensus of imaging diagnosis of DR-PB was proposed. This consensus includes clinical diagnosis and classification of DR-TB, selection of etiology and imaging examination [mainly X-ray and computed tomography (CT)], imaging manifestations, diagnosis, and differential diagnosis. This expert consensus is expected to improve the understanding of the imaging changes of DR-TB, as a starting point for timely detection of suspected DR-TB patients, and can effectively improve the efficiency of clinical diagnosis and achieve the purpose of early diagnosis and treatment of DR-TB.

Predicting occult lymph node metastasis in solid-predominantly invasive lung adenocarcinoma across multiple centers using radiomics-deep learning fusion model.

BACKGROUND: In solid-predominantly invasive lung adenocarcinoma (SPILAC), occult lymph node metastasis (OLNM) is pivotal for determining treatment strategies. This study seeks to develop and validate a fusion model combining radiomics and deep learning to predict OLNM preoperatively in SPILAC patients across multiple centers. METHODS: In this study, 1325 cT1a-bN0M0 SPILAC patients from six hospitals were retrospectively analyzed and divided into pathological nodal positive (pN+) and negative (pN-) groups. Three predictive models for OLNM were developed: a radiomics model employing decision trees and support vector machines; a deep learning model using ResNet-18, ResNet-34, ResNet-50, DenseNet-121, and Swin Transformer, initialized randomly or pre-trained on large-scale medical data; and a fusion model integrating both approaches using addition and concatenation techniques. The model performance was evaluated by the area under the receiver operating characteristic (ROC) curve (AUC). RESULTS: All patients were assigned to four groups: training set (n = 470), internal validation set (n = 202), and independent test set 1 (n = 227) and 2 (n = 426). Among the 1325 patients, 478 (36%) had OLNM (pN+). The fusion model, combining radiomics with pre-trained ResNet-18 features via concatenation, outperformed others with an average AUC (aAUC) of 0.754 across validation and test sets, compared to aAUCs of 0.715 for the radiomics model and 0.676 for the deep learning model. CONCLUSION: The radiomics-deep learning fusion model showed promising ability to generalize in predicting OLNM from CT scans, potentially aiding personalized treatment for SPILAC patients across multiple centers.

Safety and short-term outcomes of a modified valvuloplastic esophagogastrostomy versus gastric tube anastomosis after laparoscopy-assisted proximal gastrectomy: a retrospective cohort study.

BACKGROUND: There is no optimal reconstruction method after proximal gastrectomy. The valvuloplastic esophagogastrostomy can reduce postoperative reflux esophagitis, but it is technically complex with a long operation time. The gastric tube anastomosis is technically simple, but the incidences of reflux esophagitis and anastomotic stricture are higher. METHODS: We have devised a modified valvuloplastic esophagogastrostomy after laparoscopy-assisted proximal gastrectomy (LAPG), the arch-bridge anastomosis. After reviewing our prospectively maintained gastric cancer database, 43 patients who underwent LAPG from November 2021 to April 2023 were included in this cohort study, with 25 patients received the arch-bridge anastomosis and 18 patients received gastric tube anastomosis. The short-term outcomes were compared between the two groups to evaluate the efficacy of the arch-bridge anastomosis. Reporting was consistent with the STROCSS 2021 guideline. RESULTS: The median operation time was 180 min in the arch-bridge group, significantly shorter than the gastric tube group (p = 0.003). In the arch-bridge group, none of the 25 patients experienced anastomotic leakage, while one patient (4%) experienced anastomotic stricture requiring endoscopic balloon dilation. The postoperative length of stay was shorter in the arch-bridge group (9 vs. 11, p = 0.034). None of the patients in the arch-bridge group experienced gastroesophageal reflux and used proton pump inhibitor (PPI), while four (22.2%) patients in the gastric tube group used PPI (p = 0.025). The incidence of reflux esophagitis (Los Angeles grade B or more severe) by endoscopy was lower in the arch-bridge group (0% vs. 25.0%). CONCLUSION: The arch-bridge anastomosis is a safe, time-saving, and feasible reconstruction method. It can reduce postoperative reflux and anastomotic stricture incidences in a selected cohort of patients undergoing laparoscopy-assisted proximal gastrectomy.

A modified esophagogastric reconstruction method after laparoscopic proximal gastrectomy: A technical note with video vignette.

TECHNIQUE: Although the double flap technique effectively reduces the incidence of postoperative reflux esophagitis and anastomotic leakage after laparoscopic gastrectomy, its clinical application is restricted because the procedure is technical complex. We devised a modified esophagogastric reconstructive method which we termed the "arch-bridge-type" reconstruction. This reconstruction method was performed for a 71-year-old man, who was admitted to our hospital with the diagnosis of cT2N0 upper gastric cancer. The present study reported the surgical details and accompanied with the video. RESULTS: The patient underwent surgery successfully without switching to open surgery. The total operation time was 203 min, the time for making the "arch-bridge" was 16 min, and the time for esophagogastric anastomosis under laparoscopy was 23 min. No surgery-related complications occurred. The postoperative hospital stay was 10 days. The upper GI radiography demonstrated that the anastomosis was not narrow and no extravasation of contrast agent was observed. The gastroscopy found no reflux esophagitis and anastomotic stenosis 1 year after surgery. CONCLUSION: The "arch-bridge-type" reconstruction method is safe and time saving. It has advantages in simplifying the procedure of conventional double flap technique and reducing postoperative complications after proximal gastrectomy.

Lipophilic AIEgens as the "Trojan Horse" with Discrepant Efficacy in Tracking and Treatment of Mycobacterial Infection.

The highly contagious tuberculosis is a leading infectious killer, which urgently requires effective diagnosis and treatment methods. To address these issues, three lipophilic aggregation-induced emission (AIE) photosensitizers (TTMN, TTTMN, and MeOTTMN) are selected to evaluate their labeling and antimicrobial properties in vitro and in vivo. These three lipophilic AIEgens preserve low cytotoxicity and achieve real-time and non-invasive visualization of the process of mycobacteria infection in vitro and in vivo. More importantly, these AIEgens can be triggered by white light to produce reactive oxygen species (ROS), which is a highly efficient antibacterial reagent. Among these AIEgens, the TTMN photosensitizer has an outstanding antibacterial efficacy over the clinical first-line drug rifampicin at the same therapeutic concentration. Interestingly, this study also finds that TTMN can increase the expression of pro-inflammatory cytokines in the early stage of infection after light irradiation, indicating an additional pro-inflammatory role of TTMN. This work provides some feasibility basis for developing AIEgens-based agents for effectively destroying mycobacterium.

Pre- and Post-treatment Double-Sequential-Point Dynamic Radiomic Model in the Response Prediction of Gastric Cancer to Neoadjuvant Chemotherapy: 3-Year Survival Analysis.

BACKGROUND: Prognosis prediction of patients with gastric cancer after neoadjuvant chemotherapy is suboptimal. This study aims to develop and validate a dynamic radiomic model for prognosis prediction of patients with gastric cancer on the basis of baseline and posttreatment features. PATIENTS AND METHODS: This single-center cohort study included patients with gastric adenocarcinoma treated with neoadjuvant chemotherapy from June 2009 to July 2015 in the Gastrointestinal Cancer Center of Peking University Cancer Hospital. Their clinicopathological data, pre-treatment and post-treatment computed tomography (CT) images, and pathological reports were retrieved and analyzed. Four prediction models were developed and validated using tenfold cross-validation, with death within 3 years as the outcome. Model discrimination was compared by the area under the curve (AUC). The final radiomic model was evaluated for calibration and clinical utility using Hosmer-Lemeshow tests and decision curve analysis. RESULTS: The study included 205 patients with gastric adenocarcinoma [166 (81%) male; mean age 59.9 (SD 10.3) years], with 71 (34.6%) deaths occurring within 3 years. The radiomic model alone demonstrated better discrimination than the pathological T stage (ypT) stage model alone (cross-validated AUC 0.598 versus 0.516, P = 0.009). The final radiomic model, which incorporated both radiomic and clinicopathological characteristics, had a significantly higher cross-validated AUC (0.769) than the ypT stage model (0.516), the radiomics alone model (0.598), and the ypT plus other clinicopathological characteristics model (0.738; all P < 0.05). Decision curve analysis confirmed the clinical utility of the final radiomic model. CONCLUSIONS: The developed radiomic model had good accuracy and could be used as a decision aid tool in clinical practice to differentiate prognosis of patients with gastric cancer.

Development and validation of a deep learning model for multicategory pneumonia classification on chest computed tomography: a multicenter and multireader study.

Background: Accurate diagnosis of pneumonia is vital for effective disease management and mortality reduction, but it can be easily confused with other conditions on chest computed tomography (CT) due to an overlap in imaging features. We aimed to develop and validate a deep learning (DL) model based on chest CT for accurate classification of viral pneumonia (VP), bacterial pneumonia (BP), fungal pneumonia (FP), pulmonary tuberculosis (PTB), and no pneumonia (NP) conditions. Methods: In total, 1,776 cases from five hospitals in different regions were retrospectively collected from September 2019 to June 2023. All cases were enrolled according to inclusion and exclusion criteria, and ultimately 1,611 cases were used to develop the DL model with 5-fold cross-validation, with 165 cases being used as the external test set. Five radiologists blindly reviewed the images from the internal and external test sets first without and then with DL model assistance. Precision, recall, F1-score, weighted F1-average, and area under the curve (AUC) were used to evaluate the model performance. Results: The F1-scores of the DL model on the internal and external test sets were, respectively, 0.947 [95% confidence interval (CI): 0.936-0.958] and 0.933 (95% CI: 0.916-0.950) for VP, 0.511 (95% CI: 0.487-0.536) and 0.591 (95% CI: 0.557-0.624) for BP, 0.842 (95% CI: 0.824-0.860) and 0.848 (95% CI: 0.824-0.873) for FP, 0.843 (95% CI: 0.826-0.861) and 0.795 (95% CI: 0.767-0.822) for PTB, and 0.975 (95% CI: 0.968-0.983) and 0.976 (95% CI: 0.965-0.986) for NP, with a weighted F1-average of 0.883 (95% CI: 0.867-0.898) and 0.846 (95% CI: 0.822-0.871), respectively. The model performed well and showed comparable performance in both the internal and external test sets. The F1-score of the DL model was higher than that of radiologists, and with DL model assistance, radiologists achieved a higher F1-score. On the external test set, the F1-score of the DL model (F1-score 0.848; 95% CI: 0.824-0.873) was higher than that of the radiologists (F1-score 0.541; 95% CI: 0.507-0.575) as was its precision for the other three pneumonia conditions (all P values <0.001). With DL model assistance, the F1-score for FP (F1-score 0.541; 95% CI: 0.507-0.575) was higher than that achieved without assistance (F1-score 0.778; 95% CI: 0.750-0.807) as was its precision for the other three pneumonia conditions (all P values <0.001). Conclusions: The DL approach can effectively classify pneumonia and can help improve radiologists' performance, supporting the full integration of DL results into the routine workflow of clinicians.

A multicenter, randomized controlled study on the efficacy of agomelatine in ameliorating anhedonia, reduced motivation, and circadian rhythm disruptions in patients with major depressive disorder (MDD).

OBJECTIVE: To evaluate the clinical efficacy and safety of Agomelatine in improving symptoms in patients with major depressive disorder (MDD), providing more scientific evidence for the treatment of depression, and offering more effective therapeutic options for patients. METHODS: A total of 180 MDD patients in acute phase from 10 psychiatric hospitals of Grade three in Zhejiang Province were enrolled in this 12-week study with the competitive and consecutive pattern, and they were randomized into two different groups treated with flexible-dosage antidepressants of selective serotonin reuptake inhibitors (SSRI) or agomelatine, respectively. The subjects were evaluated with psychological scales of HAMD-17, HAMA, SHAPS for anhedonia, MFI-20 for fatigue, PQSI for sleep quality and MEQ for disturbances in chronobiologic rhythms at baseline, 2, 4, 8 and 12-weekend points, and TESS was used for side-effect. The results were analyzed with repeated measurement analysis of variance. RESULTS: The two groups each had 90 participants, and there were no significant differences at baseline. The scores of various assessment scales showed statistically significant time main effects during the visits (P < 0.01). The Agomelatine group demonstrated faster efficacy within 2 weeks, with better improvement in SHAPS, MEQ, and PSQI compared to the SSRIs group. However, the remission rate at 12 weeks was lower in the Agomelatine group than in the SSRIs group (63.3% and 72.2%), but the difference between the groups was not statistically significant. The Agomelatine group had fewer adverse reactions (14.4% and 16.7%), but there was a slightly higher incidence of liver function impairment (6.7% and 4.4%), with no statistically significant difference between the groups. CONCLUSION: Agomelatine, as a novel antidepressant, shows certain advantages in improving depression and anxiety symptoms and is comparable to SSRIs in terms of safety. However, its long-term efficacy and safety on MDD or other depressive subtypes still require further observation and research.

Safety and antitumour activity of cadonilimab, an anti-PD-1/CTLA-4 bispecific antibody, for patients with advanced solid tumours (COMPASSION-03): a multicentre, open-label, phase 1b/2 trial.

BACKGROUND: Immune checkpoint inhibitors targeting PD-1 or CTLA-4 individually have shown substantial clinical benefits in the treatment of malignancies. We aimed to assess the safety and antitumour activity of cadonilimab monotherapy, a bispecific PD-1/CTLA-4 antibody, in patients with advanced solid tumours. METHODS: This multicentre, open-label, phase 1b/2 trial was conducted across 30 hospitals in China. Patients aged 18 years or older with histologically or cytologically confirmed, unresectable advanced solid tumours, unsuccessful completion of at least one previous systemic therapy, and an Eastern Cooperative Oncology Group performance status of 0 or 1 were eligible for inclusion. Patients who had previously received anti-PD-1, anti-PD-L1, or anti-CTLA-4 treatment were not eligible for inclusion. In the dose escalation phase of phase 1b, patients received intravenous cadonilimab at 6 mg/kg and 10 mg/kg every 2 weeks. In the dose expansion phase of phase 1b, cadonilimab at 6 mg/kg and a fixed dose of 450 mg were given intravenously every 2 weeks. In phase 2, cadonilimab at 6 mg/kg was administered intravenously every 2 weeks in three cohorts: patients with cervical cancer, oesophageal squamous cell carcinoma, and hepatocellular carcinoma. The primary endpoints were the safety of cadonilimab in phase 1b and objective response rate in phase 2, based on the Response Evaluation Criteria in Solid Tumors (RECIST), version 1.1. The safety analysis was done in all patients who received at least one dose of cadonilimab. Antitumour activity was assessed in the full analysis set for the cervical cancer cohort, and in all patients with measurable disease at baseline and who received at least one dose of cadonilimab in the oesophageal squamous cell carcinoma and hepatocellular carcinoma cohorts. The study is registered on ClinicalTrial.gov, NCT03852251, and closed to new participants; follow-up has been completed. FINDINGS: Between Jan 18, 2019, and Jan 8, 2021, 240 patients (83 [43 male and 40 female] in phase 1b and 157 in phase 2) were enrolled. Phase 2 enrolled 111 female patients with cervical cancer, 22 patients with oesophageal squamous cell carcinoma (15 male and seven female), and 24 patients with hepatocellular carcinoma (17 male and seven female). During dose escalation, no dose-limiting toxicities occurred. Grade 3-4 treatment-related adverse events occurred in 67 (28%) of 240 patients; the most frequent grade 3 or worse treatment-related adverse events were anaemia (seven [3%]), increased lipase (four [2%]), decreased bodyweight (three [1%]), decreased appetite (four [2%]), decreased neutrophil count (three [1%]), and infusion-related reaction (two [1%]). 17 (7%) patients discontinued treatment due to treatment-related adverse events. 54 (23%) of 240 patients reported serious treatment-related adverse events, including five patients who died (one due to myocardial infarction; cause unknown for four). In phase 2, in the cervical cancer cohort, with a median follow-up of 14·6 months (IQR 13·1-17·5), the objective response rate was 32·3% (32 of 99; 95% CI 23·3-42·5). In the oesophageal squamous cell carcinoma cohort, with a median follow-up of 17·9 months (IQR 4·0-15·1), the objective response rate was 18·2% (four of 22; 95% CI 5·2-40·3). In the hepatocellular carcinoma cohort, with a median follow-up of 19·6 months (IQR 8·7-19·8), the objective response rate was 16·7% (four of 24; 95% CI 4·7-37·4). INTERPRETATION: Cadonilimab showed an encouraging tumour response rate, with a manageable safety profile, suggesting the potential of cadonilimab for the treatment of advanced solid tumours. FUNDING: Akeso Biopharma. TRANSLATION: For the Chinese translation of the abstract see Supplementary Materials section.

Seeing is believing: Efficiency evaluation of multifunctional ionic-dependent AIEgens for tuberculosis.

Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb), remains a significant public health threat with high rates of infection and mortality. Rapid and reliable theranostics of TB are essential to control transmission and shorten treatment duration. In this study, we report two cationic aggregation-inducing emission luminogens (AIEgens) named TTVP and TTPy, which have different functional charged moieties, to investigate their potential for simultaneous tracing and photodynamic therapy in TB infection. TTVP and TTPy exhibit intrinsic positive charges, excellent water solubility, and near-infrared (NIR) emission. Based on ionic-function relationships, TTVP, with more positive charges, demonstrates a stronger binding affinity to Mycobacterium marinum (M.m), (a close genetic relative of Mtb), compared to TTPy. Both TTVP and TTPy exhibit high efficiency in generating reactive oxygen species (ROS) when exposed to white light irradiation, enabling effective photodynamic killing of M.m in vitro. Additionally, we achieved long-term, real-time, noninvasive, continuous tracing, and evaluated therapeutic performance in vivo. Notably, TTVP outperformed TTPy in intracellular killing of M.m, suggesting a possible correlation between the labeling and photodynamic killing abilities of AIEgens. These findings provide valuable insights and a design basis for cationic AIEgens in TB research, offering potential advancements in TB theranostics.

An uncertainty-aware self-training framework with consistency regularization for the multilabel classification of common computed tomography signs in lung nodules.

Background: Computed tomography (CT) signs of lung nodules play an important role in indicating lung nodules' malignancy, and accurate automatic classification of these signs can help doctors improve their diagnostic efficiency. However, few relevant studies targeting multilabel classification (MLC) of nodule signs have been conducted. Moreover, difficulty in obtaining labeled data also restricts this avenue of research to a large extent. To address these problems, a multilabel automatic classification system for nodule signs is proposed, which consists of a 3-dimensional (3D) convolutional neural network (CNN) and an efficient new semi-supervised learning (SSL) framework. Methods: Two datasets were used in our experiments: Lung Nodule Analysis 16 (LUNA16), a public dataset for lung nodule classification, and a private dataset of nodule signs. The private dataset contains 641 nodules, 454 of which were annotated with 6 important signs by radiologists. Our classification system consists of 2 main parts: a 3D CNN model and an SSL method called uncertainty-aware self-training framework with consistency regularization (USC). In the system, supervised training is performed with labeled data, and simultaneously, an uncertainty-and-confidence-based strategy is used to select pseudo-labeled samples for unsupervised training, thus jointly realizing the optimization of the model. Results: For the MLC of nodule signs, our proposed 3D CNN achieved satisfactory results with a mean average precision (mAP) of 0.870 and a mean area under the curve (AUC) of 0.782. In semi-supervised experiments, compared with supervised learning, our proposed SSL method could increase the mAP by 7.6% (from 0.730 to 0.806) and the mean AUC by 8.1% (from 0.631 to 0.712); it thus efficiently utilized the unlabeled data and achieved superior performance improvement compared to the recently advanced methods. Conclusions: We realized the optimal MLC of lung nodule signs with our proposed 3D CNN. Our proposed SSL method can also offer an efficient solution for the insufficiency of labeled data that may exist in the MLC tasks of 3D medical images.

Optimization and validation of voxel size-related radiomics variability by combatting batch effect harmonization in pulmonary nodules: a phantom and clinical study.

Background: Broad generalization of radiomics-assisted models may be impeded by concerns about variability. This study aimed to evaluate the merit of combatting batch effect (ComBat) harmonization in reducing the variability of voxel size-related radiomics in both phantom and clinical study in comparison with image resampling correction method. Methods: A pulmonary phantom with 22 different types of nodules was scanned by computed tomography (CT) with different voxel sizes. The variability of voxel size-related radiomics features was evaluated using concordance correlation coefficient (CCC), dynamic range (DR), and intraclass correlation coefficient (ICC). ComBat and image resampling compensation methods were used to reduce variability of voxel size-related radiomics. The percentage of robust radiomics features was compared before and after optimization. Pathologically differential diagnosis of invasive adenocarcinoma (IAC) from adenocarcinoma in situ (AIS) and minimally invasive adenocarcinoma (MIA) (AIS-MIA group) was used for clinical validation in 134 patients. Results: Before optimization, the number of excellent features in the phantom and clinical data was 26.12% and 32.31%, respectively. The excellent features were increased after image resampling and ComBat correction. For clinical optimization, the effect of the ComBat compensation method was significantly better than that of image resampling, with excellent features reaching 90.96% and poor features only amounting to 4.96%. In addition, the hierarchical clustering analysis showed that the first-order and shape features had better robustness than did texture features. In clinical validation, the area under the curve (AUC) of the testing set was 0.865 after ComBat correction. Conclusions: The ComBat harmonization can optimize voxel size-related CT radiomics variability in pulmonary nodules more efficiently than image resampling harmonization.

Integrated Passive Sensing Chip for Highly Sensitive and Reusable Detection of Differential-Charged Nanoplastics Concentration.

In this work, a new type, highly sensitive, and reusable nanoplastics (NPs) microwave detection method is proposed, which can be used to rapidly analyze NPs with different surface charges and sizes. The effective dielectric constant of NPs varies according to the different concentrations, particle sizes, and surface charges of NPs in aqueous solution. The feasibility of the microwave method for differential-charged NPs detection is verified using a complementary split ring resonator sensor manufactured on a cost-effective printed circuit board, which shows a high sensitivity only for positively charged NPs (PS-NH2) detection. To achieve microwave detection of both positively and negatively charged NPs (PS-SO3H), a microscale spiral-coupled resonator sensing chip is manufactured through integrated passive technology, which demonstrates extremely low detection limits and high sensitivity for both PS-NH2 and PS-SO3H, with different concentrations, particle sizes, and charges. In addition, for NPs solution doped with methyl orange, the device can still perform stable measurements, overcoming the inability of traditional NPs molecular element determination and optical detection methods to detect NPs aqueous solution with organic matter doping and color presence. The proposed microwave detection method could also be extended to sensing detection for detecting other hazardous environmental substances.

A graph neural network model for the diagnosis of lung adenocarcinoma based on multimodal features and an edge-generation network.

Background: Lung cancer is a global disease with high lethality, with early screening being considerably helpful for improving the 5-year survival rate. Multimodality features in early screening imaging are an important part of the prediction for lung adenocarcinoma, and establishing a model for adenocarcinoma diagnosis based on multimodal features is an obvious clinical need. Through our practice and investigation, we found that graph neural networks (GNNs) are excellent platforms for multimodal feature fusion, and the data can be completed using the edge-generation network. Therefore, we propose a new lung adenocarcinoma multiclassification model based on multimodal features and an edge-generation network. Methods: According to a ratio of 80% to 20%, respectively, the dataset of 338 cases was divided into the training set and the test set through 5-fold cross-validation, and the distribution of the 2 sets was the same. First, the regions of interest (ROIs) cropped from computed tomography (CT) images were separately fed into convolutional neural networks (CNNs) and radiomics processing platforms. The results of the 2 parts were then input into a graph embedding representation network to obtain the fused feature vectors. Subsequently, a graph database based on the clinical and semantic features was established, and the data were supplemented by an edge-generation network, with the fused feature vectors being used as the input of the nodes. This enabled us to clearly understand where the information transmission of the GNN takes place and improves the interpretability of the model. Finally, the nodes were classified using GNNs. Results: On our dataset, the proposed method presented in this paper achieved superior results compared to traditional methods and showed some comparability with state-of-the-art methods for lung nodule classification. The results of our method are as follows: accuracy (ACC) =66.26% (±4.46%), area under the curve (AUC) =75.86% (±1.79%), F1-score =64.00% (±3.65%), and Matthews correlation coefficient (MCC) =48.40% (±5.07%). The model with the edge-generating network consistently outperformed the model without it in all aspects. Conclusions: The experiments demonstrate that with appropriate data=construction methods GNNs can outperform traditional image processing methods in the field of CT-based medical image classification. Additionally, our model has higher interpretability, as it employs subjective clinical and semantic features as the data construction approach. This will help doctors better leverage human-computer interactions.

Core-Shell Au@Nanoplastics as a Quantitative Tracer to Investigate the Bioaccumulation of Nanoplastics in Freshwater Ecosystems.

Studies on the adverse effects of nanoplastics (NPs, particle diameter <1000 nm) including physical damage, oxidative stress, impaired cell signaling, altered metabolism, developmental defects, and possible genetic damage have intensified in recent years. However, the analytical detection of NPs is still a bottleneck. To overcome this bottleneck and obtain a reliable and quantitative distribution analysis in complex freshwater ecosystems, an easily applicable NP tracer to simulate their fate and behavior is needed. Here, size- and surface charge-tunable core-shell Au@Nanoplastics (Au@NPs) were synthesized to study the environmental fate of NPs in an artificial freshwater system. The Au core enables the quantitative detection of NPs, while the polystyrene shell exhibits NP properties. The Au@NPs showed excellent resistance to environmental factors (e.g., 1% hydrogen peroxide solution, simulating gastric fluid, acids, and alkalis) and high recovery rates (>80%) from seawater, lake water, sewage, waste sludge, soil, and sediment. Both positively and negatively charged NPs significantly inhibited the growth of duckweed (Lemna minor L.) but had little effect on the growth of cyanobacteria (Microcystis aeruginosa). In addition, the accumulation of positively and negatively charged NPs in cyanobacteria occurred in a concentration-dependent manner, with positively charged NPs more easily taken up by cyanobacteria. In contrast, negatively charged NPs were more readily internalized in duckweed. This study developed a model using a core-shell Au@NP tracer to study the environmental fate and behavior of NPs in various complex environmental systems.

Efficacy of chemotherapy versus surgery as initial treatment for gastric cancer with positive peritoneal cytology.

BACKGROUND: The prognosis of gastric cancer (GC) patients with positive peritoneal cytology (CY1) without other distant metastasis is poor, and there are no standard treatment strategies. Our study aimed to compare the survival outcomes of CY1 GC patients receiving chemotherapy or surgery as initial treatment. METHODS: From February 2017 to January 2020, clinical and pathological data of patients diagnosed with CY1 GC without other distant metastasis in the Peking University Cancer Hospital was reviewed. Patients were divided into two groups: chemotherapy-initial group and surgery-initial group. In chemotherapy-initial group, patients received preoperative chemotherapy initially. According to the treatment response, the patients were divided into three subgroups: conversion gastrectomy group, palliative gastrectomy group, and further systematic chemotherapy group. In surgery-initial group, patients underwent gastrectomy followed by postoperative chemotherapy. RESULTS: A total of 96 CY1 GC patients were included with 48 patients in each group. In chemotherapy-initial group, preoperative chemotherapy yielded an objective response rate of 20.8% and disease control rate of 87.5%. Conversion to CY0 after preoperative chemotherapy was obtained in 24 (50%) patients. The median overall survival was 36.1 months in chemotherapy-initial group and 29.7 months in surgery-initial group (p = 0.367). The median progression-free survival was 18.1 months in chemotherapy-initial group and 16.1 months in surgery-initial group (p = 0.861). The 3-year overall survival rates were 50.0% and 47.9%, respectively. In chemotherapy-initial group, twenty-four patients who converted to CY0 by preoperative chemotherapy and received surgery obtained a significantly better prognosis. The median overall survival was still not reached in these patients. CONCLUSION: There was no significant difference in survival outcomes between chemotherapy-initial group and surgery-initial group. CY1 GC patients who converted to CY0 by preoperative chemotherapy and received radical surgery could obtain a favorable long-term prognosis. Further investigation should focus on preoperative chemotherapy to eliminate peritoneal cancer cell. TRIAL REGISTRATION: This study is retrospectively registered.