Development and validation of a deep learning-based model to predict response and survival of T790M mutant non-small cell lung cancer patients in early clinical phase trials using electronic medical record and pharmacokinetic data.

Background: Epidermal growth factor receptor (EGFR) T790M mutation is the standard predictive biomarker for third-generation epidermal growth factor receptor tyrosine kinase inhibitor (EGFR-TKI) treatment. While not all T790M-positive patients respond to third-generation EGFR-TKIs and have a good prognosis, it necessitates novel tools to supplement EGFR genotype detection for predicting efficacy and stratifying EGFR-mutant patients with various prognoses. Mixture-of-experts (MoE) is designed to disassemble a large model into many small models. Meanwhile, it is also a model ensembling method that can better capture multiple patterns of intrinsic subgroups of enrolled patients. Therefore, the combination of MoE and Cox algorithm has the potential to predict efficacy and stratify survival in non-small cell lung cancer (NSCLC) patients with EGFR mutations. Methods: We utilized the electronic medical record (EMR) and pharmacokinetic parameters of 326 T790M-mutated NSCLC patients, including 283 patients treated with Abivertinib in phase I (n=177, for training) and II (n=106, for validation) clinical trials and an additional validation cohort 2 comprising 43 patients treated with BPI-7711. Furthermore, 18 patients underwent whole-exome sequencing for biological interpretation of CoxMoE. We evaluated the predictive performance for therapeutic response using the area under the curve (AUC) and the Concordance index (C-index) for progression-free survival (PFS). Results: CoxMoE exhibited AUCs of 0.73-0.83 for predicting efficacy defined by best overall response (BoR) and achieved C-index values of 0.64-0.65 for PFS prediction in training and validating cohorts. The PFS of 198 patients with a low risk [median, 6.0 (range, 1.0-23.3) months in the abivertinib treated cohort; median 16.5 (range, 1.4-27.4) months in BPI-7711 treated cohort] of being non-responder increased by 43% [hazard ratio (HR), 0.56; 95% confidence interval (CI), 0.40-0.78; P=0.0013] and 50% (HR, 0; 95% CI, 0-0; P=0.01) compared to those at high-risk [median, 4.2 (range, 1.0-35) months in the abivertinib treated cohort; median, 11.0 (range, 1.4-25.1) months in BPI-7711 treated cohort]. Additionally, activated partial thromboplastin time (APTT), creatinine clearance (Ccr), monocyte, and steady-state plasma trough concentration utilited to construct model were found significantly associated with drug resistance and aggressive tumor pathways. A robust correlation was observed between APTT and Ccr with PFS (log-rank test; P<0.01) and treatment response (Wilcoxon test; P<0.05), respectively. Conclusions: CoxMoE offers a valuable approach for patient selection by forecasting therapeutic response and PFS utilizing laboratory tests and pharmacokinetic parameters in the setting of early-phase clinical trials. Simultaneously, CoxMoE could predict the efficacy of third-generation EGFR-TKI non-invasively for T790M-positive NSCLC patients, thereby complementing existing EGFR genotype detection.

Identification of the new molecular subtypes related to inflammation in breast cancer.

Breast cancer is a prevalent ailment among women, and the inflammatory response plays a crucial role in the management and prediction of breast cancer (BRCA). However, the new subtypes based on inflammation in BRCA research are still undefined. The databases including The Cancer Genome Atlas and gene expression omnibus were utilized to gather clinical data and somatic mutation information for approximately 1069 BRCA patients. Through Consensus Clustering, novel subtypes linked to inflammation were identified. A comparative analysis was conducted on the prognosis, and immune cell infiltration, and somatic mutation of the new subtypes. Additionally, an investigation into drug therapy and immunotherapy was conducted to distinguish high-risk individuals from low-risk ones. The findings of this investigation proposed the categorization of BRCA into innovative subtypes predicated on the inflammatory response and 6 key genes were a meaningful approach. Specifically, the low-, medium-, and high-inflammation subtypes exhibited varying degrees of association with clinicopathological features, tumor microenvironment, and prognosis. Notably, the high-inflammation subtype was characterized by a strong correlation with immunosuppressive microenvironments and a higher frequency of somatic mutations, which was an indication of poorer health. This study revealed that a brand-new classification could throw new light on the effective prognosis. The integration of multiple key genes was a new characterization that could promote more immunotherapy strategies and contribute to predicting the efficacy of the chemotherapeutic drugs.

Evaluation of Low-Cost CO2 Sensors Using Reference Instruments and Standard Gases for Indoor Use.

CO2 monitoring is important for carbon emission evaluation. Low-cost and medium-precision sensors (LCSs) have become an exploratory direction for CO2 observation under complex emission conditions in cities. Here, we used a calibration method that improved the accuracy of SenseAir K30 CO2 sensors from ±30 ppm to 0.7-4.0 ppm for a CO2-monitoring instrument named the SENSE-IAP, which has been used in several cities, such as in Beijing, Jinan, Fuzhou, Hangzhou, and Wuhan, in China since 2017. We conducted monthly to yearly synchronous observations using the SENSE-IAP along with reference instruments (Picarro) and standard gas to evaluate the performance of the LCSs for indoor use with relatively stable environments. The results show that the precision and accuracy of the SENSE-IAP compared to the standard gases were rather good in relatively stable indoor environments, with the short-term (daily scale) biases ranging from -0.9 to 0.2 ppm, the root mean square errors (RMSE) ranging from 0.7 to 1.6 ppm, the long-term (monthly scale) bias ranging from -1.6 to 0.5 ppm, and the RMSE ranging from 1.3 to 3.2 ppm. The accuracy of the synchronous observations with Picarro was in the same magnitude, with an RMSE of 2.0-3.0 ppm. According to our evaluation, standard instruments or reliable standard gases can be used as a reference to improve the accuracy of the SENSE-IAP. If calibrated daily using standard gases, the bias of the SENSE-IAP can be maintained within 1.0 ppm. If the standard gases are hard to access frequently, we recommend a calibration frequency of at least three months to maintain an accuracy within 3 ppm.

FF-ViT: probe orientation regression for robot-assisted endomicroscopy tissue scanning.

PURPOSE: Probe-based confocal laser endomicroscopy (pCLE) enables visualization of cellular tissue morphology during surgical procedures. To capture high-quality pCLE images during tissue scanning, it is important to maintain close contact between the probe and the tissue, while also keeping the probe perpendicular to the tissue surface. Existing robotic pCLE tissue scanning systems, which rely on macroscopic vision, struggle to accurately place the probe at the optimal position on the tissue surface. As a result, the need arises for regression of longitudinal distance and orientation via endomicroscopic vision. METHOD: This paper introduces a novel method for automatically regressing the orientation between a pCLE probe and the tissue surface during robotic scanning, utilizing the fast Fourier vision transformer (FF-ViT) to extract local frequency representations and use them for probe orientation regression. Additionally, the FF-ViT incorporates a blur mapping attention (BMA) module to refine latent representations, which is combined with the pyramid angle regressor (PAR) to precisely estimate probe orientation. RESULT: A first of its kind dataset for pCLE probe-tissue orientation (pCLE-PTO) has been created. The performance evaluation demonstrates that our proposed network surpasses other top regression networks in accuracy, stability, and generalizability, while maintaining low computational complexity (1.8G FLOPs) and high inference speed (90 fps). CONCLUSION: The performance evaluation study verifies the clinical value of the proposed framework and its potential to be integrated into surgical robotic platforms for intraoperative tissue scanning.

Integration of transcriptome, gut microbiota, and physiology reveals toxic responses of the red claw crayfish (Cherax quadricarinatus) to imidacloprid.

Imidacloprid enters the water environment through rainfall and causes harm to aquatic crustaceans. However, the potential chronic toxicity mechanism of imidacloprid in crayfish has not been comprehensively studied. In this study, red claw crayfish (Cherax quadricarinatus) were exposed to 11.76, 35.27, or 88.17 µg/L imidacloprid for 30 days, and changes in the physiology and biochemistry, gut microbiota, and transcriptome of C. quadricarinatus and the interaction between imidacloprid, gut microbiota, and genes were studied. Imidacloprid induced oxidative stress and decreased growth performance in crayfish. Imidacloprid exposure caused hepatopancreas damage and decreased serum immune enzyme activity. Hepatopancreatic and plasma acetylcholine decreased significantly in the 88.17 µg/L group. Imidacloprid reduced the diversity of the intestinal flora, increased the abundance of harmful flora, and disrupted the microbiota function. Transcriptomic analysis showed that the number of up-and-down-regulated differentially expressed genes (DEGs) increased significantly with increasing concentrations of imidacloprid. DEG enrichment analyses indicated that imidacloprid inhibits neurotransmitter transduction and immune responses and disrupts energy metabolic processes. Crayfish could alleviate imidacloprid stress by regulating antioxidant and detoxification-related genes. A high correlation was revealed between GST, HSPA1s, and HSP90 and the composition of gut microorganisms in crayfish under imidacloprid stress. This study highlights the negative effects and provides detailed sequencing data from transcriptome and gut microbiota to enhance our understanding of the molecular toxicity of imidacloprid in crustaceans.

Hai-Honghua medicinal liquor is a reliable remedy for fracture by promotion of osteogenic differentiation via activation of PI3K/Akt pathway.

ETHNOPHARMACOLOGICAL RELEVANCE: Hai-Honghua medicinal liquor (HHML), an external Chinese herbal formula preparation, is often applied to treat freshly closed tibia/fibular fractures, ankle fractures, and other bone-related disorders, but the related molecular mechanism is unclear. AIM OF THE STUDY: To evaluate the therapeutic effect of HHML in patients with tibial/fibular and ankle fractures, and to explore its related possible mechanism. METHODS AND MATERIALS: A total of 182 patients with tibia/fibular fractures and 183 patients with ankle fractures were enrolled in this study. A randomized, controlled, unblinded clinical trial was designed to evaluate the therapeutic effect of HHML on tibial/fibular and ankle fractures. The chemical compositions of HHML were analyzed by the HPLC-Q-Extractive MS/MS. Furthermore, a rat tibial fracture model was established to evaluate the therapeutic effects of HHML in promoting fracture healing, and the mouse embryonic osteoblasts cell line of MC3T3-E1 was further carried out to explore the mechanisms of HHML on osteoblast differentiation. RESULTS: In the clinical evaluation, HHML treatment significantly shortened the time for pain and swelling in patients with tibial/fibular fractures (P < 0.01) and ankle fractures (P < 0.01), and the incidence of complications was significantly reduced as well. Subsequently, 116 constituents were identified from HHML via HPLC-Q-TOF-MS/MS analysis. In vivo, no obvious changes in weight were observed in HHML-treated rats. Moreover, the levels of bone formation markers (including osteocalcin (OCN), N-terminal propeptide of type I procollagen (PINP), alkaline phosphatase (ALP), calcium (Ca) and substance P) in rat serum were significantly increased in HHML-treated rats compared with model rats (P < 0.05). Micro-CT analysis showed bone mineral density (BMD), bone volume fraction (BV/TV), trabecular thickness (Tb.Th) of the HHML-treated rats were significantly increased (P < 0.05, vs. Model) while trabecular separation (Tb.Sp) and structure model index (SMI) values were significantly reduced (P < 0.05, vs. Model). Histological analysis showed that HHML treatment promoted the healing of fractures and cartilage repair, and increased the osteoblasts and collagen fibers. Furthermore, our results also revealed HHML could promote MC3T3-E1 cells proliferation and osteoblast differentiation via regulation of the runt-related transcription factor 2 (RUNX2), bone alkaline phosphatase (BALP), and OCN by activating phosphoinositide 3-kinase/protein kinase B (PI3K/Akt) pathway, which confirmed by adding PI3K chemical inhibitor of LY294002. CONCLUSION: HHML treatment is a reliable remedy for fractures in tibial and ankle by promotion of osteogenic differentiation via activation of PI3K/Akt pathway.

Generalizable stereo depth estimation with masked image modelling.

Generalizable and accurate stereo depth estimation is vital for 3D reconstruction, especially in surgery. Supervised learning methods obtain best performance however, limited ground truth data for surgical scenes limits generalizability. Self-supervised methods don't need ground truth, but suffer from scale ambiguity and incorrect disparity prediction due to inconsistency of photometric loss. This work proposes a two-phase training procedure that is generalizable and retains the high performance of supervised methods. It entails: (1) performing self-supervised representation learning of left and right views via masked image modelling (MIM) to learn generalizable semantic stereo features (2) utilizing the MIM pre-trained model to learn robust depth representation via supervised learning for disparity estimation on synthetic data only. To improve stereo representations learnt via MIM, perceptual loss terms are introduced, which improve the model's stereo representations learnt by explicitly encouraging the learning of higher scene-level features. Qualitative and quantitative performance evaluation on surgical and natural scenes shows that the approach achieves sub-millimetre accuracy and lowest errors respectively, setting a new state-of-the-art. Despite not training on surgical nor natural scene data for disparity estimation.

Machine-learning-assisted and real-time-feedback-controlled growth of InAs/GaAs quantum dots.

The applications of self-assembled InAs/GaAs quantum dots (QDs) for lasers and single photon sources strongly rely on their density and quality. Establishing the process parameters in molecular beam epitaxy (MBE) for a specific density of QDs is a multidimensional optimization challenge, usually addressed through time-consuming and iterative trial-and-error. Here, we report a real-time feedback control method to realize the growth of QDs with arbitrary density, which is fully automated and intelligent. We develop a machine learning (ML) model named 3D ResNet 50 trained using reflection high-energy electron diffraction (RHEED) videos as input instead of static images and providing real-time feedback on surface morphologies for process control. As a result, we demonstrate that ML from previous growth could predict the post-growth density of QDs, by successfully tuning the QD densities in near-real time from 1.5 × 1010 cm-2 down to 3.8 × 108 cm-2 or up to 1.4 × 1011 cm-2. Compared to traditional methods, our approach can dramatically expedite the optimization process and improve the reproducibility of MBE. The concepts and methodologies proved feasible in this work are promising to be applied to a variety of material growth processes, which will revolutionize semiconductor manufacturing for optoelectronic and microelectronic industries.

Effect of deep neuromuscular block on the quality of early recovery after sleeve gastrectomy in obese patients: a randomized controlled trial.

BACKGROUND: Deep neuromuscular block (NMB) has been shown to improve surgical conditions and alleviate post-operative pain in bariatric surgery compared with moderate NMB. We hypothesized that deep NMB could also improve the quality of early recovery after laparoscopic sleeve gastrectomy (LSG). METHODS: Eighty patients were randomized to receive either deep (post-tetanic count 1-3) or moderate (train-of-four count 1-3) NMB. The QoR-15 questionnaire was used to evaluate the quality of early recovery at 1 day before surgery (T0), 24 and 48 h after surgery (T2, T3). Additionally, we recorded diaphragm excursion (DE), postoperative pain, surgical condition, cumulative dose of analgesics, time of first flatus and ambulation, post-operative nausea and vomiting, time of tracheal tube removal and hospitalization time. MAIN RESULTS: The quality of recovery was significantly better 24 h after surgery in patients who received a deep versus moderate block (114.4 ± 12.9 versus 102.1 ± 18.1). Diaphragm excursion was significantly greater in the deep NMB group when patients performed maximal inspiration at T2 and T3 (P < 0.05). Patients who underwent deep NMB reported lower visceral pain scores 40 min after surgery; additionally, these patients experienced lower pain during movement at T3 (P < 0.05). Optimal surgical conditions were rated in 87.5% and 64.6% of all measurements during deep and moderate NMB respectively (P < 0.001). The time to tracheal tube removal was significantly longer in the deep NMB group (P = 0.001). There were no differences in other outcomes. CONCLUSION: In obese patients receiving deep NMB during LSG, we observed improved QoR-15 scores, greater diaphragmatic excursions, improved surgical conditions, and visceral pain scores were lower. More evidence is needed to determine the effects of deep NMB on these outcomes. TRIAL REGISTRATION: ChiCTR2200065919. Date of retrospectively registered: 18/11/2022.

Identification of immune infiltration and immune-related biomarkers of periprosthetic joint infection.

Background: The immune response associated with periprosthetic joint infection (PJI) is an emerging but relatively unexplored topic. The aim of this study was to investigate immune cell infiltration in periprosthetic tissues and identify potential immune-related biomarkers. Methods: The GSE7103 dataset from the GEO database was selected as the data source. Differentially expressed genes (DEGs) and significant modular genes in weighted correlation network analysis (WGCNA) were identified. Functional enrichment analysis and transcription factor prediction were performed on the overlapping genes. Next, immune-related genes from the ImmPort database were matched. The protein-protein interaction (PPI) analysis was performed to identify hub genes. CIBERSORTx was used to evaluate the immune cell infiltration pattern. Spearman correlation analysis was used to evaluate the relationship between hub genes and immune cells. Results: A total of 667 DEGs were identified between PJI and control samples, and 1847 PJI-related module genes were obtained in WGCNA. Enrichment analysis revealed that the common genes were mainly enriched in immune and host defense-related terms. TFEC, SPI1, and TWIST2 were the top three transcription factors. Three hub genes, SDC1, MMP9, and IGF1, were identified in the immune-related PPI network. Higher levels of plasma cells, CD4+ memory resting T cells, follicular helper T cells, resting mast cells, and neutrophils were found in the PJI group, while levels of M0 macrophages were lower. Notably, the expression of all three hub genes correlated with the infiltration levels of seven types of immune cells. Conclusion: The present study revealed immune infiltration signatures in the periprosthetic tissues of PJI patients. SDC1, MMP9, and IGF1 were potential immune-related biomarkers for PJI.

Histone H3K36me3 mediates the genomic instability of Benzo[a]pyrene in human bronchial epithelial cells.

Histone modifications maintain genomic stability and orchestrate gene expression at the chromatin level. Benzo [a]pyrene (BaP) is the ubiquitous carcinogen widely spread in the environment, but the role and regulatory mechanism of histone modification in its toxic effects remain largely undefined. In this study, we found a dose-dependent reduction of histone H3 methylations at lysine4, lysine9, lysine27, lysine36 in HBE cells treated with BaP. We observed that inhibiting H3K27 and H3K36 methylation impaired cell proliferation, whereas the loss of H3K4, H3K9, H3K27, and H3K36 methylation led to increased genomic instability and delayed DNA repair. H3K36 mutation at both H3.1 and H3.3 exhibited the most significant impacts. In addition, we found that the expression of SET domain containing 2 (SETD2), the unique methyltransferase catalyzed H3K36me3, was downregulated by BaP dose-dependently in vitro and in vivo. Knockdown of SETD2 aggravated DNA damage of BaP exposure, which was consistent with the effects of H3K36 mutation. With the aid of chromatin immunoprecipitation (ChIP) -seq and RNA-seq, we found that H3K36me3 was responsible for transcriptional regulation of genes involved in pathways related to cell survival, lung cancer, metabolism and inflammation. The enhanced enrichment of H3K36me3 in genes (CYP1A1, ALDH1A3, ACOXL, WNT5A, WNT7A, RUNX2, IL1R2) was positively correlated with their expression levels, while the reduction of H3K36me3 distribution in genes (PPARGC1A, PDE4D, GAS1, RNF19A, KSR1) were in accordance with the downregulation of gene expression. Taken together, our findings emphasize the critical roles and mechanisms of histone lysine methylation in mediating cellular homeostasis during BaP exposure.

Increased risk of periprosthetic joint infection after traumatic injury in joint revision patients.

BACKGROUND: Periprosthetic joint infection (PJI) is a serious complication after total joint arthroplasty (TJA). Although some risk factors of PJI were well studied, the association between trauma and PJI remains unknown in revision patients. MATERIALS AND METHODS: Between 2015 and 2018, a total of 71 patients with trauma history before revisions (trauma cohort) were propensity score matched (PSM) at a ratio of 1 to 5 with a control cohort of revision patients without a history of trauma. Then, the cumulative incidence rate of PJI within 3 years after operation between the two groups was compared. The secondary endpoints were aseptic revisions within 3 postoperative years, complications up to 30 postoperative days, and readmission up to 90 days. During a minimal 3-year follow-up, the survival was comparatively analyzed between the trauma cohort and the control cohort. RESULTS: The cumulative incidence of PJI was 40.85% in patients with trauma history against 27.04% in the controls (P = 0.02). Correspondingly, the cumulative incidence of aseptic re-revisions was 12.68% in patients with trauma history compared with 5.07% in the control cohort (P = 0.028). Cox regression revealed that trauma history was a risk factor of PJI (HR, 1.533 [95%CI, (1.019,2.306)]; P = 0.04) and aseptic re-revisions (HR, 3.285 [95%CI, (1.790,6.028)]; P < 0.0001). CONCLUSIONS: Our study demonstrated that revision patients with trauma history carried a higher risk of PJI compared to those without trauma history. Moreover, after revisions, the trauma patients were still at higher risk for treatment failure due to PJI, periprosthetic joint fracture, and mechanical complications.

A 2-DOF drag-free control ground simulation system based on Stewart platform.

Space-based gravitational wave detection missions use multiple satellites to form a very large scale Michelson laser interferometer in space. This requires extremely high precision displacement measurements at the picometer level between test masses even millions of kilometers apart. Drag-free control is a key technology to ensure the ultra-static and ultra-stable space experiment platform for space-based gravitational wave detection. This paper proposes an innovative ground simulation scheme for drag-free control principle based on the Stewart platform. The kinematics and dynamics modeling of the Stewart platform used in the experiment is presented. A drag-free ground simulation experimental equipment is designed and built. A two-degree-of-freedom (2-DOF) drag-free controller is designed based on the H∞ loop shaping algorithm which outperforms a PID controller in Simulink simulation. A semi-physical simulation experiment is conducted to verify the controller designed using rapid control prototyping technology. The experimental results show that the control performance reaches the limit accuracy of the hardware device, thus verifying the effectiveness of the drag-free control algorithm.

Postoperative mediastinitis and sternal osteitis after cardiac surgery caused by Mycoplasma hominis: A case report.

BACKGROUND: Mediastinitis and sternal osteitis are critical complications in cardiac surgery. Cases of these complications caused by Mycoplasma hominis are extremely rare. CASE PRESENTATION: We present a case of mediastinitis and sternal osteitis caused by M. hominis infection following ascending aortic replacement surgery. Whole gene sequencing analysis suggested the genitourinary tract as the most likely source of this M. hominis infection. Successful infection control was achieved through a regimen of moxifloxacin treatment. Additionally, a notable correlation was observed between serum levels of interleukin-6 and M. hominis infection. CONCLUSIONS: The significance of M. hominis as a potential cause of postoperative infection in cardiac surgery is still not fully recognized. Special attention should be paid to patients with bacteriologically negative infections, as M. hominis should not be disregarded, despite its rarity.

The Antidepressant Effect of Magnolol on Depression-Like Behavior of CORT-Treated Mice.

Although the antidepressant-like effect of magnolol has been revealed in previous reports, the mechanism remains unclear. In this study, the antidepressant-like effect of magnolol on corticosterone-induced (CORT-induced) mice was investigated in vivo. After 21 days of CORT induction, the mice showed marked depressive-like behaviors, with a decrease in sucrose preference score and an increase in immobility time in the tail suspension test (TST) and forced swimming test (FST). Pretreatment with either magnolol (50 mg/kg, i.p.) or the kappa opioid receptor (KOR) antagonist nor-BNI (10 mg/kg, i.p.) prevented CORT-induced depression-like behavior and reduced CORT-induced dynorphin (DYN A) elevation in the hippocampal ventral DG. However, no depression-like behavior was observed in mice with KOR downregulation in the ventral DG. We further found that upregulation of DYN A in the DG caused depression-like behavior, which was blocked by intraperitoneal injection of nor-BNI and modulated by magnolol. The present study demonstrated that magnolol could ameliorate CORT-induced depression-like behaviors, by modulating the DYN A/KOR system in the ventral DG of the hippocampus.

Acoustic emission characteristics of micro-discharges in initial pulsed PEO process on 60% SiCp/Al composite.

The initial discharge process of pulsed plasma electrolytic oxidation (PEO) on the 60% SiCp/2009 aluminum metal matrix composite (Al MMC) in silicate solution was monitored by acoustic emission (AE) technique. Parameters and correlations of AE signals on the Al MMC sample and under water were analyzed, and their generation mechanism was discussed. It was found that the peak amplitudes of AE signals and AE hits during the pulse time quickly increased with the increase of micro-discharge intensity, and the absolute energy of AE signals improved several orders of magnitude. Moreover, different from the peak amplitude, duration and rise time, the duration and count had a strong correlation. Elastic stress waves resulted from the microjet of plasma bubble collapse, the inner-surface friction inside discharge channel, the expansion-shrinkage process of plasma bubbles and micro-crack propagation during rapid solidification of melt are sources of AE signals on the Al MMC sample during the pulse time. However, the expansion-shrinkage process of plasma bubbles plays a key role in the generation of underwater AE signals. In the pause time of one pulse period, the bursting and moving of vapor bubbles result in weak AE signals. It is demonstrated that the AE technique can effectively characterize the features of micro-discharges within a pulse period.

Comparison of indocyanine green-near-infrared fluorescence guided and traditional mediastinal lymphadenectomy during radical esophagectomy: A randomized controlled trial.

BACKGROUND: The extent of lymph node dissection during radical esophagectomy remains a controversial topic. Thus, this study mainly aimed to explore the location of sentinel lymph nodes in esophageal squamous cell carcinoma and the application value of the indocyanine green-near-infrared fluorescence system in lymphadenectomy. METHODS: This randomized controlled clinical trial (ClinicalTrials.gov, NCT04615806) included 42 participants without neoadjuvant therapy who were lymph node negative based on positron emission tomography/computed tomography findings. Traditional esophagectomy with indocyanine green-near-infrared fluorescence imaging was performed after injecting 0.5 mL indocyanine green (1.25 mg/mL) into the esophageal submucosa in the 4 peritumoral quadrants. The primary endpoint was to determine the location of the sentinel lymph node in esophageal squamous cell carcinoma based on postoperative pathologic reports. RESULTS: A total of 40 patients, with 20 in each group, were included in the final analysis. In the indocyanine green group, indocyanine green-near-infrared fluorescence imaging was successful in all subjects. Seven cases (cases 2, 3, 9, 11, 17, 18, and 20) in the indocyanine green group exhibited lymph node metastases, all of which were near-infrared positive. The detection rate, positive predictive value, negative predictive value, sensitivity, and specificity were 100% (20 of 20 cases), 8.7% (13/150), 100% (265/265), 100% (13/13), and 65.9% (265/402), respectively. All near-infrared-negative lymph nodes were nonmetastatic lymph nodes. In addition, the number of mediastinal lymph nodes resected in the indocyanine green group was significantly higher than in the non-indocyanine green group. CONCLUSION: Indocyanine green-near-infrared might be an important and promising technique in predicting sentinel lymph nodes of esophageal squamous cell carcinoma and could significantly improve the detection rate of lymph nodes of esophageal squamous cell carcinoma.

Fish microplastic ingestion may induce tipping points of aquatic ecosystems.

Microplastics can be ingested by a wide range of aquatic animals. Extensive studies have demonstrated that microplastic ingestion-albeit often not lethal-can affect a range of species life-history traits. However, it remains unclear how the sublethal effects of microplastics on individual levels scale up to influence ecosystem-level dynamics through cascading trophic interactions. Here we employ a well-studied, empirically fed three-species trophic chain model, which was parameterized to mimic a common type of aquatic ecosystems to examine how microplastic ingestion by fish on an intermediate trophic level can produce cascading effects on the species at both upper and lower trophic levels. We show that gradually increasing microplastics in the ingested substances of planktivorous fish may cause population structure effects such as skewed size distributions (i.e. reduced average body length vs. increased maximal body size), and induce abrupt declines in fish biomass and reproduction. Our model analysis demonstrates that these abrupt changes correspond to an ecosystem-level tipping point, crossing which difficult-to-reverse ecosystem degradation can happen. Importantly, microplastic pollution may interact with other anthropogenic stressors to reduce safe operating space of aquatic ecosystems. Our work contributes to better understanding complex effects of microplastic pollution and anticipating tipping points of aquatic ecosystems in a changing world. It also calls attention to an emerging threat that novel microplastic contaminants may lead to unexpected and abrupt degradation of aquatic ecosystems, and invites systematic studies on the ecosystem-level consequences of microplastic exposure.

Bioprinted dermis with human adipose tissue-derived microvascular fragments promotes wound healing.

Tissue-engineered skin is an effective material for treating large skin defects in a clinical setting. However, its use is limited owing to vascular complications. Human adipose tissue-derived microvascular fragments (HaMVFs) are vascularized units that form vascular networks by rapid reassembly. In this study, we designed a vascularized bionic skin tissue using a three-dimensional (3D) bioprinter of HaMVFs and human fibroblasts encapsulated in a hybrid hydrogel composed of GelMA, HAMA, and fibrinogen. Tissues incorporating HaMVFs showed good in vitro vascularization and mechanical properties after UV crosslinking and thrombin exposure. Thus, the tissue could be sutured appropriately to the wound. In vivo, the vascularized 3D bioprinted skin promoted epidermal regeneration, collagen maturation in the dermal tissue, and vascularization of the skin tissue to accelerate wound healing. Overall, vascularized 3D bioprinted skin with HaMVFs is an effective material for treating skin defects and may be clinically applicable to reduce the necrosis rate of skin grafts.

Computational-Intelligence-Based Scheduling with Edge Computing in Cyber-Physical Production Systems.

Real-time performance and reliability are two critical indicators in cyber-physical production systems (CPPS). To meet strict requirements in terms of these indicators, it is necessary to solve complex job-shop scheduling problems (JSPs) and reserve considerable redundant resources for unexpected jobs before production. However, traditional job-shop methods are difficult to apply under dynamic conditions due to the uncertain time cost of transmission and computation. Edge computing offers an efficient solution to this issue. By deploying edge servers around the equipment, smart factories can achieve localized decisions based on computational intelligence (CI) methods offloaded from the cloud. Most works on edge computing have studied task offloading and dispatching scheduling based on CI. However, few of the existing methods can be used for behavior-level control due to the corresponding requirements for ultralow latency (10 ms) and ultrahigh reliability (99.9999% in wireless transmission), especially when unexpected computing jobs arise. Therefore, this paper proposes a dynamic resource prediction scheduling (DRPS) method based on CI to achieve real-time localized behavior-level control. The proposed DRPS method primarily focuses on the schedulability of unexpected computing jobs, and its core ideas are (1) to predict job arrival times based on a backpropagation neural network and (2) to perform real-time migration in the form of human-computer interaction based on the results of resource analysis. An experimental comparison with existing schemes shows that our DRPS method improves the acceptance ratio by 25.9% compared to the earliest deadline first scheme.