Chemical-Free Recycling of Cathode Material and Aluminum Foil from Waste Lithium-Ion Batteries by Combining Plasma and Ultrasonic Technology.

With the rapid demand for lithium-ion batteries due to the widespread application of electric vehicles, a significant amount of battery electrode pieces requiring urgent treatment are generated during battery production and disposal. The strong bonding caused by the presence of binders makes it challenging to achieve thorough separation between the cathode active materials and Al foil, posing difficulties in efficient battery material recycling. To address this issue, a plasma-ultrasonically combined physical separation method is proposed in this study. This method utilizes plasma-generated excited-state radicals assisted by ultrasonic waves to separate active materials and current collectors. The results indicate that the binders are effectively decomposed under plasma treatment at 13.56 MHz, 100 W, and 10 min in an oxygen atmosphere, resulting in a separation efficiency of 96.8 wt % for the cathode materials. Characterization results demonstrate that the morphology, crystal structure, and chemical composition of the recycled cathode active materials remain unchanged, facilitating subsequent direct restoration and hydrometallurgical recycling. Simultaneously, the Al foil is also completely recycled for subsequent reuse. Compared with traditional methods of separating cathode active materials and aluminum foil, the method proposed in this study has significant economic and environmental potential. It can promote the recycling of battery materials and the development of sustainable transportation.

Multi-file dynamic compression method based on classification algorithm in DNA storage.

The exponential growth in data volume has necessitated the adoption of alternative storage solutions, and DNA storage stands out as the most promising solution. However, the exorbitant costs associated with synthesis and sequencing impeded its development. Pre-compressing the data is recognized as one of the most effective approaches for reducing storage costs. However, different compression methods yield varying compression ratios for the same file, and compressing a large number of files with a single method may not achieve the maximum compression ratio. This study proposes a multi-file dynamic compression method based on machine learning classification algorithms that selects the appropriate compression method for each file to minimize the amount of data stored into DNA as much as possible. Firstly, four different compression methods are applied to the collected files. Subsequently, the optimal compression method is selected as a label, as well as the file type and size are used as features, which are put into seven machine learning classification algorithms for training. The results demonstrate that k-nearest neighbor outperforms other machine learning algorithms on the validation set and test set most of the time, achieving an accuracy rate of over 85% and showing less volatility. Additionally, the compression rate of 30.85% can be achieved according to k-nearest neighbor model, more than 4.5% compared to the traditional single compression method, resulting in significant cost savings for DNA storage in the range of $0.48 to 3 billion/TB. In comparison to the traditional compression method, the multi-file dynamic compression method demonstrates a more significant compression effect when compressing multiple files. Therefore, it can considerably decrease the cost of DNA storage and facilitate the widespread implementation of DNA storage technology.

Zinc deficiency deteriorates ovarian follicle development and function by inhibiting mitochondrial function.

Zinc (Zn) is a crucial trace element essential for human growth and development, particularly for reproductive health. Previous research has shown a decrease in serum zinc concentration with age and individuals with conditions such as polycystic ovary syndrome (PCOS) and diabetes mellitus. However, the specific effects of zinc deficiency on the female reproductive system, especially ovarian function, are not fully understood. In our study, we observed a significant reduction in the total number of follicles and mature follicles in the zinc deficiency group. This reduction correlated with decreased level of anti-Mullerian hormone (AMH) and abnormal gene expression affecting hormone secretion regulation. Furthermore, we found that zinc deficiency disrupted mitochondrial dynamics, leading to oxidative stress in the ovaries, which further inhibited autophagy and increased ovarian apoptosis. These changes ultimately resulted in the failure of germinal vesicle breakdown (GVBD) and reduced oocyte quality. Meanwhile, administration of zinc glycine effectively alleviated the oocyte meiotic arrest caused by dietary zinc deficiency. In conclusion, our findings demonstrated that dietary zinc deficiency can affect hormone secretion and follicle maturation by impairing mitochondrial function and autophagy.

Low-Complexity 2D-DOD and 2D-DOA Estimation in Bistatic MIMO Radar Systems: A Reduced-Dimension MUSIC Algorithm Approach.

This paper presents a new technique for estimating the two-dimensional direction of departure (2D-DOD) and direction of arrival (2D-DOA) in bistatic uniform planar array Multiple-Input Multiple-Output (MIMO) radar systems. The method is based on the reduced-dimension (RD) MUSIC algorithm, aiming to achieve improved precision and computational efficiency. Primarily, this pioneering approach efficiently transforms the four-dimensional (4D) estimation problem into two-dimensional (2D) searches, thus reducing the computational complexity typically associated with conventional MUSIC algorithms. Then, exploits the spatial diversity of array response vectors to construct a 4D spatial spectrum function, which is crucial in resolving the complex angular parameters of multiple simultaneous targets. Finally, the objective is to simplify the spatial spectrum to a 2D search within a 4D measurement space to achieve an optimal balance between efficiency and accuracy. Simulation results validate the effectiveness of our proposed algorithm compared to several existing approaches, demonstrating its robustness in accurately estimating 2D-DOD and 2D-DOA across various scenarios. The proposed technique shows significant computational savings and high-resolution estimations and maintains high precision, setting a new benchmark for future explorations in the field.

Predictive role of early treatment dynamics of HBV RNA and HBcrAg for HBeAg seroconversion in children with chronic hepatitis B.

This study aimed to assess the predictive capacity of emerging serological markers, serum HBV RNA and HBcrAg, for HBeAg seroconversion in children with HBeAg-positive chronic hepatitis B (CHB). Treatment-naïve HBeAg-positive CHB children who admitted to the Liver Disease Center of Hunan Children's Hospital between April 2021 and September 2022 and received treatment with the combined entecavir and interferon-alpha treatment were recruited. Serum HBV RNA and HBcrAg were measured at baseline and Weeks 12, 24, and 48 of treatment. Our study showed that serum HBV RNA (HR = 0.71, 95% CI: 0.56-0.91, p = 0.006), HBcrAg (HR = 0.60, 95% CI: 0.43-0.84, p = 0.003), and HBsAg (HR = 0.49, 95%CI: 0.36-0.69, p < 0.001) at Week 12 were independent predictors of HBeAg seroconversion. ROC curve analysis presented that serum HBV RNA decline value (ΔHBV RNA) at Week 36 and HBcrAg decline value (ΔHBcrAg) at Week 12 (AUC = 0.871, p = 0.003 and AUC = 0.810, p = 0.003, respectively) could effectively predict HBeAg seroconversion. Furthermore, the optimal critical values were determined and the children with ΔHBV RNA > 3.759 log10 copies/mL at Week 36 or ΔHBcrAg >0.350 log10 U/mL at Week 12 more likely to achieve HBeAg seroconversion. The serum HBV RNA and HBcrAg provide new insights into the treatment of CHB in children. Early assessment of serum HBV RNA and HBcrAg during treatment can assist clinical decision-making and optimize individualized therapeutic approaches.

Transcription-related metabolic regulation in grafted lemon seedlings under magnesium deficiency stress.

Magnesium is one of the essential nutrients for plant growth, and plays a pivotal role in plant development and metabolism. Soil magnesium deficiency is evident in citrus production, which ultimately leads to failure of normal plant growth and development, as well as decreased productivity. Citrus is mainly propagated by grafting, so it is necessary to fully understand the different regulatory mechanisms of rootstock and scion response to magnesium deficiency. Here, we characterized the differences in morphological alterations, physiological metabolism and differential gene expression between trifoliate orange rootstocks and lemon scions under normal and magnesium-deficient conditions, revealing the different responses of rootstocks and scions to magnesium deficiency. The transcriptomic data showed that differentially expressed genes were enriched in 14 and 4 metabolic pathways in leaves and roots, respectively, after magnesium deficiency treatment. And the magnesium transport-related genes MHX and MRS2 may respond to magnesium deficiency stress. In addition, magnesium deficiency may affect plant growth by affecting POD, SOD, and CAT enzyme activity, as well as altering the levels of hormones such as IAA, ABA, GA3, JA, and SA, and the expression of related responsive genes. In conclusion, our research suggests that the leaves of lemon grafted onto trifoliate orange were more significantly affected than the roots under magnesium-deficient conditions, further indicating that the metabolic imbalance of scion lemon leaves was more severe.

MI-MZI based distributed optical fiber sensor for location and pattern recognition.

This research addressed the drawbacks of the conventional hybrid structure and processing technique by presenting a novel distributed fiber optic sensor based on a hybrid Michelson and Mach-Zehnder interferometer. The sensor can achieve blind spot free positioning and has a wide response frequency, additionally its structure is not complex. It can obtain two phase signals from each of the two interferometers by using a demodulation method that uses a 3 × 3 optical coupler. To determine the position of the disturbance, we computed cross-correlations on the two signals following basic mathematical techniques. Markov Transition Field was used to transform the phase signals-which had been filtered by a band pass filter-into two-dimensional images. Tagged photos built a dataset, which is then fed into a neural network to identify patterns. Experiments have shown that the frequency response capacity of the structure was verified, and it was able to achieve location within 0-30 km with location errors of ±85 m. In a six-category pattern recognition, the testing set accuracy was 98.74%.

DeepLION2: deep multi-instance contrastive learning framework enhancing the prediction of cancer-associated T cell receptors by attention strategy on motifs.

Introduction: T cell receptor (TCR) repertoires provide valuable insights into complex human diseases, including cancers. Recent advancements in immune sequencing technology have significantly improved our understanding of TCR repertoire. Some computational methods have been devised to identify cancer-associated TCRs and enable cancer detection using TCR sequencing data. However, the existing methods are often limited by their inadequate consideration of the correlations among TCRs within a repertoire, hindering the identification of crucial TCRs. Additionally, the sparsity of cancer-associated TCR distribution presents a challenge in accurate prediction. Methods: To address these issues, we presented DeepLION2, an innovative deep multi-instance contrastive learning framework specifically designed to enhance cancer-associated TCR prediction. DeepLION2 leveraged content-based sparse self-attention, focusing on the top k related TCRs for each TCR, to effectively model inter-TCR correlations. Furthermore, it adopted a contrastive learning strategy for bootstrapping parameter updates of the attention matrix, preventing the model from fixating on non-cancer-associated TCRs. Results: Extensive experimentation on diverse patient cohorts, encompassing over ten cancer types, demonstrated that DeepLION2 significantly outperformed current state-of-the-art methods in terms of accuracy, sensitivity, specificity, Matthews correlation coefficient, and area under the curve (AUC). Notably, DeepLION2 achieved impressive AUC values of 0.933, 0.880, and 0.763 on thyroid, lung, and gastrointestinal cancer cohorts, respectively. Furthermore, it effectively identified cancer-associated TCRs along with their key motifs, highlighting the amino acids that play a crucial role in TCR-peptide binding. Conclusion: These compelling results underscore DeepLION2's potential for enhancing cancer detection and facilitating personalized cancer immunotherapy. DeepLION2 is publicly available on GitHub, at https://github.com/Bioinformatics7181/DeepLION2, for academic use only.

Subarachnoid haemorrhage-induced reversible cardiac dysfunction: time course and potential mechanisms.

AIMS: Cardiac dysfunction is commonly observed in patients with subarachnoid haemorrhage (SAH). However, the specific timeline of cardiac remodelling and the underlying mechanisms responsible for this effect following SAH remain unknown. This study aims to explore the impact of SAH on cardiac dysfunction and its potential mechanisms over time. METHODS AND RESULTS: In Protocol 1, we investigated cardiac function and potential mechanisms in a Sprague-Dawley rat model of SAH at six time points (baseline and Days 1, 3, 7, 14, and 28) while exploring the underlying mechanisms. Our assessments included the haemodynamic profile, echocardiography, and the concentrations of plasma biomarkers at various time points post-SAH. We determined neuropeptide Y (NPY) 1-5 receptor protein expression levels through western blotting. In Protocol 2, we administered an NPY1 receptor antagonist to evaluate the effects of cardiac dysfunction induced by SAH on Day 3. In Protocol 1, SAH gradually provoked cardiac systolic dysfunction during the acute phase, reaching its peak on Day 3 without concurrent alterations in wall thickness. However, no significant changes were observed from Days 14 to 28 compared with Day 0. The changes in cardiac dysfunction were consistent with myocardial injury, inflammatory biomarkers, and NPY levels. SAH resulted in a heightened heart rate and systolic blood pressure, correlating with elevated epinephrine and norepinephrine levels. In Protocol 2, the administration of the NPY1 receptor antagonist effectively ameliorated cardiac dysfunction. CONCLUSIONS: SAH induces transient cardiac dysfunction in the acute phase, and the underlying mechanisms for this response involve the NPY-NPY1 receptor pathway, otherwise known as catecholamines.

Internal Vanadium Doping and External Modification Design of P2-Type Layered Mn-Based Oxides as Competitive Cathodes toward Sodium-Ion Batteries.

P2-type layered manganese-based oxides have attracted considerable interest as economical, cathode materials with high energy density for sodium-ion batteries (SIBs). Despite their potential, these materials still face challenges related to sluggish kinetics and structural instability. In this study, a composite cathode material, Na0.67Ni0.23Mn0.67V0.1O2@Na3V2O2(PO4)2F was developed by surface-coating P2-type Na0.67Ni0.23Mn0.67V0.1O2 with a thin layer of Na3V2O2(PO4)2F to enhance both the electrochemical sodium storage and material air stability. The optimized Na0.67Ni0.23Mn0.67V0.1O2@5wt %Na3V2O2(PO4)2F exhibited a high discharge capacity of 176 mA h g-1 within the 1.5-4.1 V range at a low current density of 17 mA g-1. At an increased current density of 850 mA g-1 within the same voltage window, it still delivered a substantial initial discharge capacity of 112 mAh g-1. These findings validate the significant enhancement of ion diffusion capabilities and rate performance in the P2-type Na0.67Ni0.33Mn0.67O2 material conferred by the composite cathode.

Characteristics and clinical treatment outcomes of chronic hepatitis B children with coexistence of hepatitis B surface antigen (HBsAg) and antibodies to HBsAg.

BACKGROUND: The coexistence of hepatitis B surface antigen (HBsAg) and hepatitis B surface antibody (HBsAb) represents an uncommon serological pattern observed in patients with hepatitis B virus (HBV) infection, and its underlying mechanism and clinical significance have not been well established. The aim of this study was to investigate the association between this serological profile and clinical treatment outcomes in children with chronic hepatitis B (CHB). METHODS: This retrospective cohort study included 372 treatment-naïve CHB children from the Hunan Children's Hospital. The participants were categorized into HBsAb-positive group and HBsAb-negative group. The associations between HBsAb positive status to clinical outcomes were assessed using Cox proportional hazard regression. Receiver operating characteristic curve was conducted to evaluate the prediction ability in HBsAg loss. RESULTS: The coexistence of HBsAg and HBsAb accounted for 23.39% (87/372) of the participants. The crude incidence rates of HBsAg loss, hepatitis B e antigen (HBeAg) clearance, and HBV-DNA undetectability were higher in the HBsAb-positive group compared with the HBsAb-negative group (37.46 vs. 17.37, 49.51 vs. 28.66, 92.11 vs. 66.54 per 100 person-years, respectively, all P < 0.05). The Cox regression analysis revealed a significant association between this serological profile and an increased likelihood of HBsAg loss (HR = 1.78, P = 0.001), and HBeAg clearance (HR = 1.78, P = 0.001). In addition, a combination of HBsAb ≥ 0.84 log10 IU/L and age ≤ 5 years can help identify patients likely to achieve HBsAg loss after antiviral therapy, with an AUC of 0.71. CONCLUSIONS: Children who are positive for both HBsAg and HBsAb demonstrate a higher probability of favorable outcomes after antiviral treatment. Thus, children with HBsAb-positive CHB should be actively treated to achieve functional cure.

Retinoic acid alleviates rotavirus-induced intestinal damage by regulating redox homeostasis and autophagic flux in piglets.

Rotaviruses (RV) are a major cause of severe gastroenteritis, particularly in neonatal piglets. Despite the availability of effective vaccines, the development of antiviral therapies for RV remains an ongoing challenge. Retinoic acid (RA), a metabolite of vitamin A, has been shown to have anti-oxidative and antiviral properties. However, the mechanism by which RA exerts its intestinal-protective and antiviral effects on RV infection is not fully understood. The study investigates the effects of RA supplementation in Duroc × Landrace × Yorkshire (DLY) piglets challenged with RV. Thirty-six DLY piglets were assigned into six treatments, including a control group, RA treatment group with two concentration gradients (5 and 15 mg/d), RV treatment group, and RV treatment group with the addition of different concentration gradients of RA (5 and 15 mg/d). Our study revealed that RV infection led to extensive intestinal architecture damage, which was mitigated by RA treatment at lower concentrations by increasing the villus height and villus height/crypt depth ratio (P < 0.05), enhancing intestinal stem cell signaling and promoting intestinal barrier functions. In addition, 15 mg/d RA supplementation significantly increased NRF2 and HO-1 protein expression (P < 0.05) and GSH content (P < 0.05), indicating that RA supplementation can enhance anti-oxidative signaling and redox homeostasis after RV challenge. Additionally, the research demonstrated that RA exerts a dual impact on the regulation of autophagy, both stimulating the initiation of autophagy and hindering the flow of autophagic flux. Through the modulation of autophagic flux, RA influence the progression of RV infection. These findings provide new insights into the regulation of redox hemostasis and autophagy by RA and its potential therapeutic application in RV infection.

Size-Dependent Response of Hydrothermally Grown SnO2 for a High-Performance NO2 Sensor and the Impact of Oxygen.

A NO2 sensor with a detection limit down to the ppb level based on pristine SnO2 has been developed through a facile poly(acrylic acid)-mediated hydrothermal method. SnO2 particles of solid microsphere, hollow microsphere, and nanosphere morphologies were synthesized, with respective constitutional crystallite of size ∼2 µm in length and 10-20 nm and ∼7 nm in diameter. All sensors show great selectivity to NO2. The hollow microsphere sensor exhibits the best performance, with medium specific surface area (SSA), followed by the nanosphere sensor with the largest SSA. This is attributed to the superposition of two opposite effects on sensor response with increased SSA: more adsorption sites and fewer electrons to be taken out with overly small crystallite that may reach complete depletion. O2 is found to speed up the response and recovery times but reduce the response because O adsorbates facilitate the adsorption/desorption of NO2 thermodynamically, and the two oxidizing gases compete in harvesting electrons from SnO2. The adverse effect of humidity can be minimized by operating the sensor at 110 °C. The response of the hollow microsphere sensor to 50 ppb of NO2 is 8.8 (Rg/Ra) at room temperature, and it increases to 15.1 at 110 °C. These findings are useful for developing other oxidizing gas semiconductor sensors.

O-GlcNAcylation orchestrates porcine oocyte maturation through maintaining mitochondrial dynamics and function.

O-linked ß-N-acetylglucosamine (O-GlcNAc) modification exists widely in cells, playing a crucial role in the regulation of important biological processes such as transcription, translation, metabolism, and the cell cycle. O-GlcNAc modification is an inducible reversible dynamic protein post-translational modification, which regulates complex cellular activities through transient glycosylation and deglycosylation. O-GlcNAc glycosylation is specifically regulated by O-GlcNAc glycosyltransferase (O-GlcNAc transferase, OGT) and O-GlcNAc glycoside hydrolase (O-GlcNAcase). However, the mechanisms underlying the effects of O-GlcNAc modification on the female reproductive system, especially oocyte quality, remain unclear. Here, we found that after OGT was inhibited, porcine oocytes failed to extrude the first polar body and exhibited abnormal actin and microtubule assembly. Meanwhile, the mitochondrial dynamics and function were also disrupted after inhibition of OGT function, resulting in the occurrence of oxidative stress and autophagy. Collectively, these results inform our understanding of the importance of the glycosylation process for oocyte maturation, especially for the maturation quality of porcine oocytes, and the alteration of O-GlcNAc in oocytes to regulate cellular events deserves further investigation.

A prospective, single-arm trial of PD-1 inhibitors plus chemoradiotherapy for solitary metachronous metastasis nasopharyngeal carcinoma.

PURPOSE: Initial treatment for Recurrent/Metastatic Nasopharyngeal Carcinoma (R/M NPC) often involves Gemcitabine plus cisplatin with or without PD-1 inhibitors. However, PD-1 inhibitors' effectiveness varies, prompting for better treatments. This study explores effect and safety of combining PD-1 inhibitors with chemoradiotherapy for oligometastatic NPC patients. METHODS: Oligometastatic NPC patients underwent radical treatment with PD-1 inhibitors and chemotherapy, followed by concurrent PD-1 inhibitors and chemoradiotherapy, and then maintenance PD-1 inhibitors. Objective response rate (ORR) and disease control rate (DCR) were calculated by irRECIST-1.1, and CTCAE-4.0 was used to evaluate the toxicity. RESULTS: The study enrolled 47 patients with a median age of 46. The median follow-up lasted 16.5 months, with metastatic lesions receiving a median radiation dose of 45 Gy. The median courses of PD-1 inhibitors and chemotherapy were 9.5 and 5 respectively. The metastasis sites included lung (40.8 %), liver (21.1 %), mediastinal lymph node (7.9 %), abdominal lymph nodes (3.9 %), bone (21.1 %), adrenal gland (3.9 %), and brain (1.3 %). ORR and DCR were 85.1 % and 100 % at 3 months after radiotherapy. The median survival was not reached yet, and 1 and 2-year OS rates were 93.1 % and 78.4 %. The median PFS was 18 months, with 1 and 2-year PFS rates of 70.2 % and 47.7 % respectively. PD-L1 expression showed a positive correlation for PFS. Twenty-five patients experienced grade 3 or 4 adverse events (AE) that were possibly related to chemotherapy. No grade 5 AE was observed. CONCLUSIONS: The synergy of concurrent PD-1 inhibitors and chemoradiotherapy shows promising efficacy and an acceptable toxicity for oligometastasis NPC patients.

Cardiovascular toxicities following the use of tyrosine kinase inhibitors in hepatocellular cancer patients: a retrospective, pharmacovigilance study.

BACKGROUND: Cardiac adverse events (AEs) are common in tyrosine kinase inhibitors(TKIs). This study explored the cardiac AEs of TKIs through the Food and Drug Administration's Adverse Event Reporting System (FAERS). METHODS: Disproportionality analysis and Bayesian analysis were utilized for data mining of the suspected cardiac AEs of TKIs, based on FAERS data from January 2004 to December 2021. RESULTS: A total of 4708 cardiac AEs reports of sorafenib, regorafenib, lenvatinib, and cabozantinib were identified. Hypertension accounts for the most reported cardiac AE. Lenvatinib appears to induce cardiac failure with the highest signals strength [ROR = 7.7 (3.46,17.17)]. Acute myocardial infarction was detected in lenvatinib [ROR = 7.91 (5.64,11.09)] and sorafenib [ROR = 2.22 (1.74, 2.84)]. Acute coronary syndrome was detected in lenvatinib [ROR = 11.57 (6.84, 19.58)] and sorafenib [ROR = 2.81 (1.87,4.24)]. Atrial fibrillation was detected in sorafenib [ROR = 1.82 (1.55,2.14)] and regorafenib [ROR = 1.36 (1.03,1.81)]. Meanwhile, aortic dissections were detected in sorafenib [ROR = 5.08 (3.31,7.8)] and regorafenib [ROR = 3.39 (1.52,7.56)]. Most patients developed hypertension and cardiac failure within 30 days of initiating TKI treatments. Patients taking lenvatinib had an increased incidence of developing acute coronary syndrome after 180 days of treatment. CONCLUSION: Analysis of FAERS data provides a precise profile on the characteristics of cardiac AEs associated with different TKI regimens. Distinct monitoring and appropriate management are needed in the care of TKI recipients.

Analysis of the Correlation and Prognostic Significance of Tertiary Lymphoid Structures in Breast Cancer: A Radiomics-Clinical Integration Approach.

BACKGROUND: Tertiary lymphoid structures (TLSs) are potential prognostic indicators. Radiomics may help reduce unnecessary invasive operations. PURPOSE: To analyze the association between TLSs and prognosis, and to establish a nomogram model to evaluate the expression of TLSs in breast cancer (BC) patients. STUDY TYPE: Retrospective. POPULATION: Two hundred forty-two patients with localized primary BC (confirmed by surgery) were divided into BC + TLS group (N = 122) and BC - TLS group (N = 120). FIELD STRENGTH/SEQUENCE: 3.0T; Caipirinha-Dixon-TWIST-volume interpolated breath-hold sequence for dynamic contrast-enhanced (DCE) MRI and inversion-recovery turbo spin echo sequence for T2-weighted imaging (T2WI). ASSESSMENT: Three models for differentiating BC + TLS and BC - TLS were developed: 1) a clinical model, 2) a radiomics signature model, and 3) a combined clinical and radiomics (nomogram) model. The overall survival (OS), distant metastasis-free survival (DMFS), and disease-free survival (DFS) were compared to evaluate the prognostic value of TLSs. STATISTICAL TESTS: LASSO algorithm and ANOVA were used to select highly correlated features. Clinical relevant variables were identified by multivariable logistic regression. Model performance was evaluated by the area under the receiver operating characteristic (ROC) curve (AUC), and through decision curve analysis (DCA). The Kaplan-Meier method was used to calculate the survival rate. RESULTS: The radiomics signature model (training: AUC 0.766; test: AUC 0.749) and the nomogram model (training: AUC 0.820; test: AUC 0.749) showed better validation performance than the clinical model. DCA showed that the nomogram model had a higher net benefit than the other models. The median follow-up time was 52 months. While there was no significant difference in 3-year OS (P = 0.22) between BC + TLS and BC - TLS patients, there were significant differences in 3-year DFS and 3-year DMFS between the two groups. DATA CONCLUSION: The nomogram model performs well in distinguishing the presence or absence of TLS. BC + TLS patients had higher long-term disease control rates and better prognoses than those without TLS. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 2.

Detecting Abnormality of Battery Lifetime from First-Cycle Data Using Few-Shot Learning.

The service life of large battery packs can be significantly influenced by only one or two abnormal cells with faster aging rates. However, the early-stage identification of lifetime abnormality is challenging due to the low abnormal rate and imperceptible initial performance deviations. This work proposes a lifetime abnormality detection method for batteries based on few-shot learning and using only the first-cycle aging data. Verified with the largest known dataset with 215 commercial lithium-ion batteries, the method can identify all abnormal batteries, with a false alarm rate of only 3.8%. It is also found that any capacity and resistance-based approach can easily fail to screen out a large proportion of the abnormal batteries, which should be given enough attention. This work highlights the opportunities to diagnose lifetime abnormalities via "big data" analysis, without requiring additional experimental effort or battery sensors, thereby leading to extended battery life, increased cost-benefit, and improved environmental friendliness.

Efficient treatment of surfactant containing wastewater by photocatalytic ozonation with BiPO4 nanorods.

In this study, monoclinic BiPO4 nanorods were fabricated by one-pot solvothermal method. Its catalytic capability in photocatalytic ozonation process was tested by degradation and mineralization of sodium dodecyl benzene sulfonate (SDBS) solution. The results demonstrated that the TOC removal rate was dramatically improved to 90.0% at 75 min for UV/O3/BiPO4 process, which was 4.9 and 3.8 times more than that of UV/BiPO4 and O3. Moreover, the pseudo-first-order kinetic constant (0.337 min-1) and mineralization rate (90.0%) for SDBS degradation using BiPO4 in UV/O3 process were 1.6 and 1.3 times as great as that of conventional TiO2 photocatalyst (0.206 min-1, 67.3%). The influence of BiPO4 dosage, O3 concentration initial pH and coexisted ions on SDBS degradation in UV/O3/BiPO4 process were also investigated. The outcome of quenching studies illustrated both ·OH and h+ contributed prominently to SDBS degradation in UV/O3/BiPO4 process, implying that high valence band position of BiPO4 could promote the synergism between photocatalysis and ozonation. The degradation pathway of SBDS was proposed by combination of intermediates analysis and DFT calculation. Real carwash wastewater was chosen as typical surfactant containing wastewater to explore the practical application of UV/O3/BiPO4 technology. During 30 min, COD and LAS removal efficiency reached 59.7% and 70.6%, respectively. The quality indices of effluent could meet the requirements for reuse of carwash water in Water Quality Standard for Urban Miscellaneous Use in China. Energy consumption in the process was calculated as 13.9 kW h m-3, which was about 3.6 and 2.2 times less than that of UV/BiPO4 and O3 process, respectively. The results suggest that UV/O3/BiPO4 system has an application potential for surfactant containing wastewater treatment or recycle.

Room-Temperature CuI-Catalyzed N-Arylation of Cyclopropylamine.

A general and efficient CuI/N-carbazolyl-1H-pyrrole-2-carbohydrazide catalyst system was developed for the N-arylation of cyclopropylamine using aryl bromides at room temperature. Herein, 5 mol % CuI and 5 mol % of the ligand were used to synthesize N-aryl cyclopropylamines in moderate to excellent yields. This protocol was scaled up to produce the desired product at gram levels and has been generalized for C-N coupling between aryl bromides and amines at room temperature.