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Scene parsing, or semantic segmentation, aims at labeling all pixels in an image with the predefined categories of things and stuff. Learning a robust representation for each pixel is crucial for this task. Existing state-of-the-art (SOTA) algorithms employ deep neural networks to learn (discover) the representations needed for parsing from raw data. Nevertheless, these networks discover desired features or representations only from the given image (content), ignoring more generic knowledge contained in the dataset. To overcome this deficiency, we make the first attempt to explore the meaningful supportive knowledge, including general visual concepts (i.e., the generic representations for objects and stuff) and their relations from the whole dataset to enhance the underlying representations of a specific scene for better scene parsing. Specifically, we propose a novel supportive knowledge mining module (SKMM) and a knowledge augmentation operator (KAO), which can be easily plugged into modern scene parsing networks. By taking image-specific content and dataset-level supportive knowledge into full consideration, the resulting model, called knowledge augmented neural network (KANN), can better understand the given scene and provide greater representational power. Experiments are conducted on three challenging scene parsing and semantic segmentation datasets: Cityscapes, Pascal-Context, and ADE20K. The results show that our KANN is effective and achieves better results than all existing SOTA methods.

Background Observational studies have shown promising therapeutic effects of long-pulsed neodymium-doped yttrium aluminum garnet (LP-Nd:YAG) laser on warts. Objective To evaluate whether LP-Nd:YAG laser was superior to cryotherapy for cutaneous warts. Methods In this study, 150 adult patients with warts were randomized equally to receive laser or cryotherapy every 3–4 weeks, a maximum of 4 sessions. The primary outcomes were cure rate at 16 weeks and 6 months; secondary outcomes included time to clearance of warts and treatment-related adverse effects. Results There was no difference in the cure rate for laser versus cryotherapy at 16 weeks (54.1% vs. 46.7%) and 6 months (59.5% vs. 57.3%). However, time to clearance of warts, up to 16 weeks and 6 months, tended to be shorter for laser versus cryotherapy ( P = .04 and .08, respectively). Post-hoc analyses showed a significantly higher cure rate for laser versus cryotherapy in 3 subgroups of HPV 2/27/57-induced recalcitrant warts, but not in their counterpart subgroups. Laser had more mild adverse effects. Limitations Single-center. Conclusions The overall therapeutic effects of LP-Nd:YAG laser were similar to cryotherapy, but laser may be more effective to relatively recalcitrant warts and may associate with shorter time to clearance of warts.

Advances in the development of anti-tumour drugs and related technologies have resulted in a significant increase in the number of cancer survivors. However, the incidence of chemotherapy-induced cardiotoxicity (CIC) has been rising continuously, threatening their long-term survival. The integration of nanotechnology and biomedicine has brought about an unprecedented technological revolution and has promoted the progress of anti-tumour therapy. In this review, we summarised the possible mechanisms of CIC, evaluated the role of nanoparticles (including liposomes, polymeric micelles, dendrimers, and hydrogels) as drug carriers in preventing cardiotoxicity and proposed five advantages of nanotechnology in reducing cardiotoxicity: Liposomes cannot easily penetrate the heart's endothelial barrier; optimized delivery strategies reduce distribution in important organs, such as the heart; targeting the tumour microenvironment and niche; stimulus-responsive polymer nano-drug carriers rapidly iterate; better economic benefits were obtained. Nanoparticles can effectively deliver chemotherapeutic drugs to tumour tissues, while reducing the toxicity to heart tissues, and break through the dilemma of existing chemotherapy to a certain extent. It is important to explore the interactions between the physicochemical properties of nanoparticles and optimize the highly specific tumour targeting strategy in the future.

Objective This study aimed to investigate the demographic and clinicopathological characteristics, and survival outcomes of subglottic Squamous Cell Carcinoma (SCC) based on the Surveillance, Epidemiology, and End Results (SEER) database. Methods Demographic and clinicopathological information, including age, sex, race, tumor size, histologic grade, clinical/TNM stage, tumor invasion extent, Lymph Node Metastasis (LNM) extent, size of metastatic lymph nodes, LNM ratio and treatment data, of 842 subglottic SCC patients diagnosed between 1996 and 2016 were acquired. Kaplan-Meier survival analyses were performed to assess the effects of clinicopathological characteristics, treatment modalities, surgical procedures, and adjuvant therapies on overall survival and cancer-specific survival. Results Subglottic SCC was more frequent among males aged 60-70 years, with low-grade but locally advanced lesions without local or distant metastases. Age and several primary tumor/LNM related variables were independent risk factors for overall survival and cancer specific survival. Advanced-stage and high-grade disease led to unfavorable prognosis. The most common treatment modality and surgical procedure were surgery plus radiotherapy and total laryngectomy, respectively. Surgery plus radiotherapy provided favorable 5-year survival outcomes, while total laryngectomy had the worst. Surgery plus adjuvant therapy showed better survival outcomes than surgery alone. Conclusion This study confirmed the rarity of subglottic SCC. Patients with subglottic SCCs suffered poor prognosis especially for those with advanced-stage or high-grade lesions. The prognosis of subglottic SCC remained poor over the years, despite recent progress in cancer therapies. Surgery plus adjuvant therapy improved the survival outcome. Although larynx preservation surgery was beneficial for early-stage disease, total laryngectomy was favored for patients with advanced tumors. Level of evidence Level 4.

With the aggressive and amazing scaling of the feature size of semiconductors, hotspot detection has become a crucial and challenging problem in the generation of optimized mask design for better printability. Machine learning techniques, especially deep learning, have attained notable success on hotspot detection tasks. However, most existing hotspot detectors suffer from suboptimal performance due to two-stage flow and less efficient representations of layout features. What is more, most works can only solve simple benchmarks with apparent hotspot patterns like ICCAD 2012 Contest benchmarks. In this paper, we firstly develop a new end-to-end hotspot detection flow where layout feature embedding and hotspot detection are jointly performed. An attention mechanism-based deep convolutional neural network is exploited as the backbone to learn embeddings for layout features and classify the hotspots simultaneously. Experimental results demonstrate that our framework achieves accuracy improvement over prior arts with fewer false alarms and faster inference speed on much more challenging benchmarks.

In this work, we design an iterative deep neural network to solve full-wave inverse scattering problems in the 2D case. Forward modeling neural networks that predict the scattered field are embedded in an inversion neural network. In an iterative manner, the inversion network predicts the model update from the residual between the simulated data and the observed data. The proposed inversion network can achieve super-resolution reconstruction, meanwhile keeping the simulated data of reconstructed models well consistent with the observed data. We validate this method with both synthetic and experimental data inversion. Results show that the inversion network can predict models with high accuracy, efficiency, and good generalization ability. By combining deep learning and physical simulation together, the proposed method provides a way for real-time imaging with high reliability and accuracy.

Purpose Anti-CD19 chimeric antigen receptor T-cell immunotherapy (19CAR-T) has achieved impressive clinical results in adult and pediatric relapsed/refractory (r/r) B-lineage acute lymphoblastic leukemia (B-ALL). However, the application and effect of CAR-T therapy in B-ALL patients with extramedullary relapse are rarely issued even disqualified in some clinical trials. Here, we examined the efficacy of 19CAR-T in patients with both bone marrow and extramedullary involvement. Materials and methods CAR-T cells were generated by transfection of primary human T lymphocytes with a lentiviral vector expressing anti-CD19 single chain antibody fragments (scFvs) with the cytoplasmic domains of 4-1BB and CD3ζ, and used to infuse patients diagnosed as having r/r B-ALL with extramedullary origination. Clinical responses were evaluated by the use of bone marrow aspiration, imaging, and flow cytometry. Results Eight patients received 19CAR-T infusion and all attained complete remission (CR). Only one patient was bridged to hematopoietic stem cell transplantation (HSCT). Although three patients relapsed after infusion, they received 19/22CAR-T infusion sequentially and attained a second remission. To date, five patients are in continuous CR and all eight patients are still alive. The mean follow-up time was 21.9 months, while the 24-month estimated event-free survival is 51.4%. Conclusion Anti-CD19 CAR-T therapy can lead to clinical remission for extramedullary relapsed pediatric B-ALL patients. However, the problem of CD19+ relapses after CAR-T remained to be solved. For patients relapsing after CAR-T, a second CAR-T therapy creates another opportunity for remission for subsequent HSCT.

A 24 GHz self-calibrated all-digital frequency-modulated continuous-wave (FMCW) synthesizer is presented in this article. A multi-bank digitally controlled oscillator (DCO) is employed to provide adequate frequency tuning range and high frequency resolution. A full background self-calibration scheme is proposed to linearize the DCO tuning curve for highly linear and fast chirp generation. An overlap compensator based on an adaptive lookup table (LUT) is utilized to eliminate the frequency overlaps between adjacent DCO tuning bands. The compensation words in the LUT are altered by least-mean-square (LMS) algorithm for robust and precise matching. A ramp tracker, which features real-time ramp tracking with zero steady-state phase error, is employed to estimate and stabilize the frequency ramp. Implemented in 40 nm bulk CMOS, the FMCW synthesizer prototype consumes 28 mW with a 0.26 mm² core area. The maximum chirp bandwidth is 3.2 GHz, corresponding to 13.33% of the center frequency. Measurement results show that the root-mean-square (RMS) frequency error is reduced by 1/10 with self-calibration after 2 ms convergence time. The maximum chirp slope is up to 320 MHz/μs with 309 kHz RMS frequency error. The minimum RMS frequency error is 7.35 kHz under 5 MHz/μs chirp slope, corresponding to 0.0002% of the chirp bandwidth.

This paper presents a recursive feature elimination (RFE) mechanism to select the most informative genes with a least square kernel extreme learning machine (LSKELM) classifier. Describing the generalization ability of LSKELM in a way that is related to small norm of weights, we proposed a ranking criterion to evaluate the importance of genes by the norm of weights obtained by LSKELM network. The proposed method is called LSKELM-RFE algorithm, which first employs the original genes to build a LSKELM classifier, and then ranks the genes according to their importance given by the norm of LSKELM network output weights, and finally removes a least important gene. Benefiting from the random mapping mechanism of the extreme learning machine (ELM) kernel, there are no parameter of LSKELM-RFE needs to be manually tuned. A comparative study among our proposed algorithm and other two famous RFE algorithms has shown that LSKELM-RFE outperforms other RFE algorithms in both the computational cost and generalization ability.

Microgrids, gaining traction from rising distributed generation for carbon reduction, demand novel solutions to regulate on-and off-grid operations, as well as both energy and monetary transfers between the microgrid and the central grid and among different microgrid participants. This research aims to develop and validate an intelligent microgrid management system to secure the competitiveness of Singapore's energy market, by leveraging the inherent synergy between two emerging technologies, i.e., blockchain for Peer-to-Peer (P2P) solar power trading and fog computing for grid infrastructure management. For this vision, we have developed FogChain, an integrative, cost-effective, and scalable microgrid operating system (MGOS), consisting of three technical service layers: 1) a novel microgrid information infrastructure based on the fog-computing paradigm (i.e., intelligence on edge); 2) a blockchain-based microgrid service layer, providing smart contract and decentralized control capabilities for grid application development; and 3) a microgrid application layer (i.e., P2P energy trading) over the blockchain-based grid service. This MGOS would fundamentally transform how solar power is traded among participating electricity prosumers, leading to potentially new operational and business models. We have implemented the FogChain system and conducted extensive experiments to verify its performance advantages. Our results demonstrate that FogChain can efficiently process energy auction among 1000 participants with 1.1 s delay on average, reduce transmission cost up to 20% under the loss-aware trading mechanism, and reduce the solar yield prediction error to 0.11. Our system prototype suggests that FogChain provides a promising solution for efficient decentralized energy trading and intelligent distributed control for microgrids. Energy Market Authority (EMA) Ministry of Education (MOE) National Research Foundation (NRF) This work was supported in part by the National Research Foundation, Singapore, and the Energy Market Authority through Energy Programme under EP Award NRF2017EWT-EP003-023, and in part by the MOE through Tier-1 Grant Call under Award RG96/20.

As the circuit feature size continuously shrinks down, hotspot detection has become a more challenging problem in modern DFM flows. Developed deep learning techniques have recently shown their superiorities on hotspot detection tasks. However, existing hotspot detectors can only handle defect detection from one small layout clip each time, thus may be very time-consuming when dealing with a large full-chip layout. In this paper, we develop a new end-to-end framework that can detect multiple hotspots in a large region at a time and promise a better hotspot detection performance. We design a joint auto-encoder and inception module for efficient feature extraction. A two-stage classification and regression framework is designed to detect hotspot with progressive accurate localization, which provides a promising performance improvement. Experimental results show that our framework enables a significant speed improvement over existing methods with higher accuracy and fewer false alarms.

Photoelectrochemical (PEC) water-splitting using solar energy holds great promise for the renewable energy future, and a key challenge in the development of industry viable PEC devices is the unavailability of high-efficient photoanodes. Herein, we designed a TiO2 model photocatalyst with nano-groove pattern and different surface orientation using low-energy Ar+ irradiation and photoetching of TiO2, and significantly improved the intrinsic activity for PEC water oxidation. High-resolution transmission electron microscopy directly manifests that the grooves consist of highly stepped surface with steps and well-crystallized. Transient absorption spectroscopy reveals the groove surface that allows for increased recovery lifetime, which ensures promoted electron-hole separation efficiency. Surface photovoltage directly shows the carrier separation and transportation behaviors, verified by selective photodeposition, demonstrating the groove surface on TiO2 contributes to electron-hole separation. This work proposes an efficient and scalable photoanode strategy, which potentially can open new opportunities for achieving efficient PEC water oxidation performance.

Background: The development of cancer drugs is among the most focused “bench to bedside activities” to improve human health. Because of the amount of data publicly available to cancer research, drug development for cancers has significantly benefited from big data and Artificial Intelligence (AI). In the meantime, challenges, like curating the data of low quality, remain to be resolved. Objective: This review focused on the recent advancements in and challenges of AI in developing cancer drugs. Method: We discussed target validation, drug repositioning, de novo design, and compounds' synthetic strategies. Results and Conclusion: AI can be applied to all stages during drug development, and some excellent reviews detailing the applications of AI in specific stages are available.

The action mechanism of pollutants in solar-water evaporation (SWE) is a crucial scientific issue in the utilization of sewage resources. A single-atom copper-carbon system (Cu/SA) was used for the first time in SWE for utilization of sewage resources. Experiments and theoretical calculations show that atomic-level dispersed Cu-N coordination promotes carrier orientation migration. Electron-rich Cu sites with high carrier concentrations can enhance the localized surface plasmon resonance (LSPR) and thus enhance the nonradiative relaxation energy release. The suitable adsorption energy of single-atom copper sites for H2O could effectively promote the evaporation of water. Benefiting from these effects, Cu/SA achieves a high water evaporation rate (3.325 kg/m2·h under 2 suns). The action mechanism of various pollutants in SWE is explored. The metal ions in sewage can be deposited by photogenerated electron reduction, which enhances the light absorption properties. Dyes with a visible light absorption capability can increase the light absorption performance. Electron-donating organics can facilitate water evaporation process by promoting photogenerated carrier separation. A variety of sewage can be effectively resourced to produce clean water. This study can provide a fundamental scientific understanding of the behavior mechanism of pollutants in SWE, thus providing viable technical support for wastewater resource utilization.

Purpose: With the emergence of multidrug-resistant and pan-resistant strains, Klebsiella pneumoniae (K. pneumoniae) shows higher treatment failure rates and mortality in clinics. It is more important to develop an effective method for treating K. pneumonia infections. The main objectives of this study were to determine the minimal inhibitory concentration (MIC) and the mutant prevention concentration (MPC) for eight antimicrobial agents against K. pneumoniae isolated from different hosts and compare the emergence of resistant mutants between animal strains and human strains. Materials and Methods: A total of 72 nonduplicate K. pneumoniae isolates and 8 antimicrobial agents (amikacin, azithromycin, levofloxacin, doxycycline, nitrofurantoin, colistin, tigecycline, and imipenem) were used. The MIC and MPC values were determined using agar plate assays. The values of the selection index (SI) were calculated with MPC90/MIC90. Pharmacodynamic parameters were calculated using published plasma pharmacokinetic variables. Results: For human isolate strains, the MPC50/90 (μg/mL) values were as follows: amikacin, 32/128; azithromycin, 64/128; levofloxacin, 4/16; doxycycline, 32/32; nitrofurantoin, 128/512; colistin, 4/8; tigecycline, 8/16; and imipenem, 4/8. The value of SI was 8 for azithromycin, doxycycline, and tigecycline; 16 for amikacin, levofloxacin, and nitrofurantoin; 4 for imipenem; and 2 for colistin. For animal isolate strains, the MPC90 values were 128 μg/mL for azithromycin and doxycycline, 64 μg/mL for amikacin, 32 μg/mL for levofloxacin, 512 μg/mL for nitrofurantoin, 8 μg/mL for colistin and tigecycline, 4 μg/mL for imipenem. The value of SI was 2 for colistin and imipenem, 8 for tigecycline, 16 for amikacin, and 32 for the other four agents. In combination with pharmacokinetic parameters, these findings indicated that the plasma concentrations of the seven antibiotics except imipenem were below the MPC for the entire dosing interval. Conclusion: The ability of eight antibiotics to prevent resistant mutants of K. pneumoniae was different between animal strains and human strains. Higher doses than those currently approved should be required to prevent the enrichment of mutants of drug-resistant bacteria in the clinics.

Herein, we explored effects of miR-93-5p and gluconeogenic rate-limiting enzyme PCK1 on HCC cells. Bioinformatics analysis and cell experiments confirmed that, compared with expression in normal tissue and cells, miR-93-5p in HCC was abnormally upregulated while PCK1 expression was remarkably downregulated. PCK1 overexpression repressed proliferation, migration, and invasion of HCC cells, and blocked cell cycle in G0/G1 phase. During this process, glucose production was boosted while the production of pyruvate, lactic acid, citric acid, and malic acid was reduced, suggesting that the effect was related to inhibition of glycolysis and induction of gluconeogenic pathways. Elevated miR-93-5p level promoted proliferation, migration, and invasion of HCC cells, accelerated development of cell cycle, activated glycolysis, and suppressed gluconeogenesis. In addition, when miR-93-5p and PCK1 were concurrently upregulated, the abovementioned promoting effects were canceled out. These investigations demonstrated that promoting effect of miR-93-5p on HCC cell growth may be carried out by inhibiting the PCK1 expression, suggesting that miR-93-5p and PCK1 could be applied as new biomarkers or novel therapeutic targets for HCC diagnosis.

Highway crack segmentation is a critical task for highway infrastructure monitoring and maintenance. While imagery from unmanned aerial vehicles (UAVs) is applied to the task of highway crack segmentation, it has great prospects in terms of speed and range. However, it is difficult to accurately identify road cracks from UAV remote sensing images, because the cracks are very narrow and small, often containing only a few pixels. To improve the segmentation of road cracks in UAV images, this study proposed an improved identification technique based on the U-Net architecture enhanced with a convolutional block attention module, an improved encoder and the strategy of fusing long and short skip connections. A public road crack dataset was relabelled for network training and a UAV remote sensing road crack dataset containing 1157 images was used to verify the generalisation ability of the enhanced network model. Results showed that the proposed method could effectively predict highway cracks in UAV images, with mIoU of 77.47 % and crack accuracy of 68.38%, which was better than the traditional U-Net model and some traditional semantic segmentation models. The proposed network is trained quickly by public dataset and can predict the road cracks on the new UAV images with high crack accuracy. This study provides an effective solution for the need to quickly grasp the damage status of roads over a wide area in the case of earthquake and other natural disasters. The highway crack segmentation benchmark dataset will be open sourced after the manuscript is accepted at: https://github.com/zhhongsh/UAV-Benchmark-Dataset-for-Highway-Crack-Segmentation.

Frequent nightmares are related to depressive symptoms in adolescents. Little is known about pathways from frequent nightmares to depressive symptoms. This study aimed to examine the mediation effect of nightmare distress in the association between frequent nightmares and depressive symptoms in a large sample of Chinese adolescents.A total of 11,831 adolescents who participated in the baseline survey of Shandong Adolescent Behavior and Health Cohort were included in the analysis. A self-administered questionnaire was used to measure nightmare frequency, nightmare distress, depressive symptoms, sleep duration, insomnia, and demographic characteristics. Linear regressions and mediation analyses were performed to examine the associations between frequent nightmares, nightmare distress and depressive symptoms.Of 11,831 participates, 50.9% were males and the mean age was 14.97 ± 1.45. Adolescents with frequent nightmares scored significantly higher on nightmare distress (t = 29.87, P 0.001) and depressive symptoms (t = 20.05, P 0.001) than those adolescents without frequent nightmares. Frequent nightmares (β = 1.04, 95% CI: 0.48-1.60) and nightmare distress (β = 0.30, 95% CI: 0.28-0.32) were associated with depressive symptoms. Mediation analyses showed that nightmare distress accounted for 63.76% of the total effects in the entire sample, 51.17% in males and 80.00% in females, respectively.No causality could be made from the cross-sectional data and possible information bias due to self-report.The association between frequent nightmares and depressive symptoms appears to be substantially mediated by nightmare distress. Assessing and intervening distress associated with frequent nightmares may have important clinical implications for reducing the risk of depression in adolescents.

Formation of p-n junction was an effective method to improve the photocatalytic performance due to its built-in electric field. However, the electric field was distributed only on the interface between two semiconductors, which was insufficient in comparison to the entire material. In this work, a multilayer TiO2–CoTiO3 p-n junction was designed and fabricated by atomic layer deposition. The charge transport and photoelectrochemical properties of multilayer TiO2–CoTiO3 films of various thicknesses are thoroughly investigated. The PL and electrochemical tests demonstrate that TiO2–CoTiO3 exhibits enhanced charge separation and transport. Additionally, the extra visible light response was achieved by introduction of CoTiO3. Also, theoretical calculations indicate that the electrons prefer to immigrate from TiO2 to CoTiO3 in a multilayer TiO2–CoTiO3 structure. Benefited from the boosted light absorption and charge transfer, the multilayer TiO2–CoTiO3 composite film exhibits a significantly increased photocurrent, much higher than pure TiO2 and a single TiO2–CoO p-n junction. This multilayer p-n junction structure opens a rational and novel way for nanostructure construction in the energy conversion region.

This article presents a thermal control design method for a surface acoustic wave (SAW) device. We designed a heat-dissipation structure and packaging scheme to solve three key issues observed in SAW devices using anisotropic crystals as piezoelectric substrates in acoustofluidics (e.g., lithium niobate): SAW chip cracking caused by thermal stress, SAW chip cracking caused by mismatched thermal expansion coefficients of the packaging materials, and enhancement of the structural strength and stability of the SAW chip. This study establishes the physical model of the designed structure and the relationship between the steady-state working temperature and the physical properties of the material. By comparing these physical properties and numerical calculations, we identified nanosilver adhesive as the most effective bonding material between the SAW chip and the heat sink. In addition to designing and fabricating, we also evaluated our SAW devices experimentally. The results not only confirmed that the abovementioned three key problems were solved but also demonstrated the significant enhancement of the stability of the SAW device.

Herpes zoster (HZ) is a disease caused by the reactivation of the varicella zoster virus. Postherpetic neuralgia (PHN) is the most common complication of HZ.Repetitive paravertebral block with local anaesthetics and dexmedetomidine for the prevention of PHN in patients with acute herpes zoster.104 patients with acute herpes zoster were randomly divided into two groups. Group Rop received repetitive paravertebral block with 0.25% ropivacaine 20 ml per 72 h three times. Group Dex received repetitive paravertebral block with a mixture of 0.25% ropivacaine 20 ml and dexmedetomidine 20 µg per 72 h three times. Patients were permitted to take tramadol when the visual analogue scale (VAS) ≥ 4. The incidence of zoster-related pain was recorded at 1, 3, and 6 months after the end of treatments; VAS scores and the dose of rescue drug were recorded at 1 week, 2 weeks, 1 month, 3 months, and 6 months after the end of treatments.At 1 month post therapy, the incidence of zoster-related pain was 11% in Group Dex, compared with 35% in Group Rop (Repetitive paravertebral block with local anaesthetics and dexmedetomidine in patients with acute herpes zoster can significantly reduce the incidence of zoster-related pain.

Phase variations of the interrogation field lead to frequency shifts in Ramsey-type atomic clocks. This paper reports the development of a 300 MHz Mach–Zehnder (MZ) switch that effectively suppresses phase-transient effects. Similar to MZ interferometers, this radio-frequency (RF) MZ switch comprises two arms that are power- and phase-matched with each other. By inserting a PIN diode RF switch in one arm, the other arm remains undisturbed, freeing it of the phase transient. Trigger phase fluctuation measurements are implemented by using a lock-in amplifier to extract the in-phase and quadrature (I/Q) demodulation data. The results show that the extinction ratio of the RF MZ switch phase fluctuations is −16.

Background and aim Coronavirus disease 2019 (COVID-19) is a life-threatening disease that predominantly causes respiratory failure. The impact of COVID-19 on other organs remains elusive. Herein, we aimed to investigate the effects of COVID-19 on the hepatobiliary system. Methods In the current study, we obtained the clinical records and laboratory results from 66 laboratory-confirmed patients with COVID-19 at the Wuhan Tongji Hospital between 10 February 2020 and 28 February 2020. The detailed clinical features and laboratory findings were collected for analysis. Bioinformatics analysis was conducted to evaluate the correlation between gamma-glutamyl transferase (GGT) and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) entry receptor angiotensin-converting enzyme 2 (ACE2). Results In this cohort, 30 (51.7%) patients had abnormal liver function on admission, which was associated with disease severity and enriched in the male and diabetic patients. The elevated levels of direct bilirubin (P = 0.029) and GGT (P = 0.004) were common in patients with severe pneumonia when compared with those with mild pneumonia. In addition, elevated levels of GGT (P = 0.003) and aspartate aminotransferase (AST) (P = 0.007) were positively associated with longer hospital stay. The expression of ACE2 was closely associated with GGT in various human tissues because they shared the common transcriptional regulator hepatic nuclear factor-1β (HNF1B). Conclusions Increased GGT levels were common in severe cases and elevated GGT levels were positively associated with prolonged hospital stay and disease severity. Due to the consistent expression with ACE2, GGT is a potent biomarker indicating the susceptibility of SARS-CoV-2 infection.

PURPOSE To compare outcomes after arthroscopy in FAIS patients with preoperative asymptomatic gluteal tendinosis (GT) to a control group with no gluteal tendinosis. METHODS A retrospective analysis was performed using data from FAIS patients who had arthroscopy between 2016 and 2018. Asymptomatic GT was diagnosed using hip MRI without clinical symptoms. Patients with asymptomatic GT were 1:1 propensity-score matched to patients without GT. Patient-reported outcomes (HOS-ADL, iHOT-12, mHHS), VAS scores, radiographic measures, performed procedures, complications, and revision surgery were compared and analyzed for both groups. RESULTS A total of 105 asymptomatic GT hips and 105 hips without GT were found using propensity-score matching. When compared to preoperative levels, both groups demonstrated significant improvements in PROs and VAS scores at the final follow-up. Besides, there were no significant differences in preoperative scores, final outcome scores, or score improvements between the groups. Patients in the GT group were significantly less likely to achieve the MCID for the VAS score (72.4% vs 83.8%, p = 0.045). However, there were no other differences in the rate of meeting the PASS and MCID between the study and the control groups. CONCLUSION It was demonstrated in this study that FAIS patients with asymptomatic gluteal tendinosis can expect to experience similar good short-term patients-reported outcomes as compared with patients without gluteal tendinosis. LEVEL OF EVIDENCE III.

ACE2 has long been known as an injury protective protein, which can protect against a variety of organ damage such as the heart, liver, kidney, and lung. Especially in cardiovascular diseases, as a negative regulator of RAAS, ACE2 is an extremely important protective factor that mainly plays a role by converting Ang II to Ang-(1-7). Nevertheless, with the recent outbreak of COVID-19, it is exposed that another identity of ACE2 is the entry receptor for SARS-CoV-2, which previously serves as the entry receptor for SARS. With the in-depth clinical research, it is found that the severity and susceptibility of COVID-19 are related to cardiovascular diseases, and SARS-CoV-2 binding to ACE2 receptor is also potentially associated with heart injury symptoms. Therefore, in this article, we mainly summarize the relationship between ACE2, COVID-19, and cardiovascular diseases/heart injury.

The significant penetration of renewable energy resources and ever-rising load demand has gradually aggravated the safe operation of the interconnected power system. A generalized extended state observer and fractional-order theory based integral sliding mode control strategy is introduced in the interconnected power system to minimize the frequency deviation by controlling the governor of the generation unit. The generalized extended state observer is designed to estimate the disturbance from system uncertainty, load demand, and wind power fluctuation to improve the robustness of the interconnected power system. The fractional-order integral sliding mode control relieves the chattering of frequency deviation and tie-line power deviation. Besides, the superconducting magnetic energy storage and the wind model, as the ancillary frequency regulation devices, are implemented in the interconnected power system. The novel sliding mode controller based on generalized extended state observer is designed for the interconnected power system with the addition of the superconducting magnetic energy storage and the wind model. Stability proof and simulation comparison with the integer-order sliding mode control and other three control schemes are carried out as well.

Teniposide, as a more potent inhibitor of topoisomerase II compared with etoposide, shows less damage on hematopoietic stem cells. Few data are available on teniposide in hematopoietic stem cell transplantation (HSCT) for high-risk or refractory recurrent hematopoietic malignant diseases, particularly for acute myeloid leukemia (AML).A retrospective single arm study was conducted to confirm the feasibility of teniposide (300 mg/m2) -intensified HSCT in the treatment of high-risk or refractory recurrent hematopoietic malignant disease by analysing the outcomes of 32 patients, who received transplantation between January 2016 and December 2018. Univariate and multivariate analyses were performed to evaluate prognostic factors of the endpoints. Statistically significant factors (P0.05) in multivariate analyses were regarded to be predictive.All patients achieved myeloid engraftment at a median of 13 days (range, 9-28 days), platelet engraftment at 15.5 days (range, 6-142 days), with a cumulative incidence (CI) of platelet engraftment of 93.75%±0.26%. The CI of grade II-IV acute graft versus host disease (aGVHD) was 43.75%±0.80% and that of grade III-IV aGVHD 12.50%±0.35%. The CI of chronic (c)GVHD was 74.07%±0.82% and that of extensive cGVHD 33.33%±0.87%. The CI of relapse was 35.03%±0.76%. The one-year probability of overall survival (OS) was 62.50%±0.09%, while 2-year OS was 46.90%±0.09%, and those of 1- and 2-year leukemia-free-survival (LFS) were 56.30%±0.09% and 46.90%±0.09%, respectively. Generally, the OS and LFS until the end of our follow up were 43.50%±0.09% and 34.80%±0.11%, respectively. The probability of GVHD-free and relapse-free survival (GRFS) was 24.60%±0.08%. Multivariate analysis indicated that the probability of OS was significantly lower in patients with a disease duration of more than 280 days before receiving HSCT and in those with fewer mononuclear cells. For LFS, other than the above two factors, failure to achieve complete response (CR) before HSCT was another independent risk factor. Similarly, the probability of GRFS was significantly lower in patients with longer disease duration (≥280 days) and those receiving stem cells from female donors.For patients with high-risk or refractory recurrent hematopoietic malignant disease, teniposide-based conditioning regimens followed by allo-HSCT can be considered as an alternative therapy with encouraging prognoses.

As a unique group of advanced artificial materials, metamaterials have found many interesting applications in various devices due to the ability to control electromagnetic fields. The metamaterial provides the prospect of new opportunities for the wireless power transfer (WPT) system to improve efficiency and reduce magnetic flux density. This review paper evaluates the performance of the WPT system with metamaterial from both principles and functions aspects. The objectives of this review include: (1) to present the research process and bottlenecks of metamaterial in the WPT system; (2) to clarify the design solution and checking method of the metamaterial and (3) to identify the challenges and opportunities based on the functional of the WPT system integration with metamaterial. Therefore, the process on metamaterial design, working principle of metamaterial, optimal method, equivalent model, and experimental method are reviewed. The recent efforts of the WPT system with metamaterial in efficiency enhancement, misalignments, magnetic field reduction are illustrated. Finally, the challenges and prospects of metamaterial based on the WPT system are concluded.

A method to derive topologies of four-quadrant dual-dc-port dual-buck inverter (DDP-DBI) is proposed in this article. A new family of DDP-DBIs is obtained by replacing one of the switching legs in a four-quadrant dual-buck half-bridge switching cell with a dual-input buck type switching leg. With the proposed DDP-DBIs, both the low voltage dc source and the high voltage intermediate dc-bus can be used as the inputs of the inverter. Therefore, in comparison with the conventional two-stage dc–ac power system, a semi-two-stage dc–ac power conversion system with reduced power losses and enhanced conversion efficiency is achieved. A unipolar sinusoidal pulse width-modulation strategy is presented for the DDP-DBI. In each line cycle, all the power devices and filter inductors only operate within half line cycle, and only one active switch is operated at high frequency. Moreover, no freewheeling current flows through the body diodes of the active switches. As a result, the conversion efficiency of the overall dc–ac power conversion system is improved. Operation principles, characteristics, modulation and control strategies of one of the proposed DDP-DBI are analyzed in detail. Effectiveness and feasibility of the proposed DDP-DBI are verified with experimental results.

Communicating health knowledge effectively at the community level is essential for shaping resilient urban governance in a pandemic period. This paper examines how three styles of community health communication, namely traditional authoritative communication (TAC), authoritative communication via social media (ACSM), and interactive communication via social media (ICSM), were associated with public trust in different types of “institutions”, namely the community administration and scientists, in a context where the respondents were in strict lockdown. This research was conducted with an online survey in February 2020 of 4595 respondents in urban China not long after the strict lockdown was introduced. Embedded in the theory of public trust in institutions during pandemic, the regressions established that traditional authoritative communication played a significant role in maintaining the public's trust in both community administrators and scientists. Interactive communication via social media damaged trust in scientists and increased trust in administrators when used effectively. It is suggested that policymakers, government officials, and healthcare professionals should not abandon traditional authoritative health communication, and greater efforts can be devoted to quality improvement. Moreover, the study highlighted the need to gain a better understanding of what the targeted audience perceive to be “good communication” before communication.

The study of natural gas migration and accumulation of tight gas has become the focus of the energy industry in recent years. One of the priorities is the research of hydrocarbon migration carrier system of the formation. This study reveals two types of hydrocarbon carrier systems (micro-fractures and micro-coal lines) in the tight formation through a large amount of geological observations, data statistics, and simulations. This study also first put forward the view that the coal lines can be a type of hydrocarbon carrier system in tight sandstone formation. During the research process, an improved permeability testing method and apparatus are used to test the core permeability widely. Based on the real core, three models are established to describe the micro-fracture/micro-coal line characteristics. According to the three typical models, the Voronoi method is used to rebuild the network models. The migration and accumulation process in tight formation is simulated with the Multiple Relaxation Time lattice Boltzmann method in numerical simulation and with displacement apparatus in physical simulation. The results indicate that the micro-fracture/micro-coal line will significantly improve the percolation capacity of sandstone as the hydrocarbon migration carrier system in tight formation, the mechanism is revealed by numerical simulations. The micro-fractures/micro-coal lines are favorable for natural gas accumulation in tight formation. Unlike the conventional formation, in tight formation, micro-fractures/micro-coal lines tend to be the main migration carrier systems during the gas accumulation process.

Previous research has investigated whether hyperuricemia serves as an independent risk factor for cardiovascular and renal diseases. Hyperuricemia is defined as an abnormally high level of uric acid (UA; i.e., serum urate level > 6.8 mg/dL). Hyperuricemia has been considered a complication of chronic kidney disease (CKD). However, it seems to play a pathogenic role in the progression of renal diseases. There has been increasing focus on the link between hyperuricemia and CKD. The results of randomized controlled trials have implied independent associations between hyperuricemia and the progression of cardiovascular and renal morbidities. These associations may be mediated by renin-angiotensin system activation, nitric oxide synthase inhibition, and macrovascular/microvascular disease development. There remains controversy regarding the use of serum UA level as an indirect index of renal vascular disease. This literature review focuses on the role of asymptomatic hyperuricemia in the progression of CKD, as well as the association between hyperuricemia and cardiovascular disease. It also provides a general overview of the physiological metabolism of UA.

Objective: Patients with non–small cell lung cancer (NSCLC) respond differently to cytokine-induced killer cell (CIK) treatment. Therefore, potential prognostic markers to identify patients who would benefit from CIK treatment must be elucidated. The current research aimed at identifying predictive prognostic markers for efficient CIK treatment of patients with NSCLC. Methods: Patients histologically diagnosed with NSCLC were enrolled from the Tianjin Medical University Cancer Institute and Hospital. We performed whole-exome sequencing (WES) on the tumor tissues and paired adjacent benign tissues collected from 50 patients with NSCLC, and RNA-seq on tumor tissues of 17 patients with NSCLC before CIK immunotherapy treatment. Multivariate Cox proportional hazard regression analysis was used to analyze the association between clinical parameters and prognostic relevance. WES and RNA-seq data between lung squamous cell carcinoma (SCC) and adenocarcinoma (Aden) were analyzed and compared. Results: The pathology subtype of lung cancer was the most significantly relevant clinical parameter associated with DFS, as analyzed by multivariate Cox proportional hazard regression (P = 0.031). The patients with lung SCC showed better CIK treatment efficacy and extended DFS after CIK treatment. Relatively low expression of HLA class II genes and checkpoint molecules, and less immunosuppressive immune cell infiltration were identified in the patients with lung SCC. Conclusions: Coordinated suppression of the expression of HLA class II genes and checkpoint molecules, as well as less immune suppressive cell infiltration together contributed to the better CIK treatment efficacy in lung SCC than lung Aden.

A cost-effective totem-pole power factor correction converter with high-frequency gallium nitride high electron-mobility transistors and low-frequency Si diodes is investigated in this article. The reverse recovery characteristics of low-frequency diodes are evaluated experimentally. With the slow recovery characteristics, a negative current can flow through the low frequency diode, so that soft-switching and critical mode operation is achieved easily. However, if the duration of the negative current exceeds the reverse recovery time of the low-frequency diode, the diode will switch at high frequency, leading to severe losses and losing control of the inductor current. In order to avoid this issue, an adaptive off-time soft-switching strategy is adopted, and discontinuous conduction mode operation is suggested near the zero crossing of the grid voltage. Furthermore, since only the low-frequency grid current is sampled, this control strategy has the merits of low requirements on control resources and low cost. Experimental results of a 400W prototype are provided to verify the effectiveness of the proposed control strategy.

Silicon nitride (SiN) waveguides with ultra-low optical loss enable integrated photonic applications including low noise, narrow linewidth lasers, chip-scale nonlinear photonics, and microwave photonics. Lasers are key components to SiN photonic integrated circuits (PICs), but are difficult to fully integrate with low-index SiN waveguides due to their large mismatch with the high-index III-V gain materials. The recent demonstration of multilayer heterogeneous integration provides a practical solution and enabled the first-generation of lasers fully integrated with SiN waveguides. However, a laser with high device yield and high output power at telecommunication wavelengths, where photonics applications are clustered, is still missing, hindered by large mode transition loss, non-optimized cavity design, and a complicated fabrication process. Here, we report high-performance lasers on SiN with tens of milliwatts output power through the SiN waveguide and sub-kHz fundamental linewidth, addressing all the aforementioned issues. We also show Hertz-level fundamental linewidth lasers are achievable with the developed integration techniques. These lasers, together with high-Q SiN resonators, mark a milestone towards a fully integrated low-noise silicon nitride photonics platform. This laser should find potential applications in LIDAR, microwave photonics and coherent optical communications., Achieving high output power and low noise integrated lasers is a major challenge. Here the authors experimentally demonstrate integrated lasers from a Si/SiN heterogeneous platform that shows Hertz-level linewidth, paving the way toward fully integrating low-noise silicon nitride photonics in volume using real devices for lasing.

Many studies have demonstrated that acupuncture combined with Chinese herbal medicine (CHM) effectively treats knee osteoarthritis (KOA), with few side effects. However, few systematic reviews have offered evidence-based support. Here we conducted a meta-analysis on the combination of acupuncture with CHM in treating KOA.Databases including CNKI, Wanfang, VIP, PubMed, EMBASE, and Cochrane library were systematically searched for articles on the treatment of KOA by acupuncture combined with CHM from the establishment of the database to May 2021. Three researchers independently searched, screened, extracted, and included articles that met the inclusion standards. The primary outcome measure was overall response rate (ORR), and the secondary outcome measures included Visual Analogue Scale (VAS) score, Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) score, and Lysholm score. ORR was a binary variable, while other indicators were continuous variables. The quality of literature was assessed with a modified Jadad scale. The RevMan 5.3 software provided by the Cochrane Collaboration was used for statistical analysis.Thirty-three randomized controlled trials involving 3,954 patients were included. Meta-analysis showed that ORR [odds ratio (OR) =5.41; 95% confidence interval (CI): (4.38, 6.68); P0.00001], VAS score [mean difference (MD) =-1.86; 95% CI: (-2.44, -1.29); P0.00001], WOMAC score [MD =-13.05; 95% CI: (-21.70, -4.41); P=0.003], and Lysholm score [MD =10.47; 95% CI: (5.21, 15.72); P0.0001] in the combination group were significantly superior to those in the control group.Compared with acupuncture alone or CHM/Western drug alone, acupuncture combined with CHM can effectively alleviate knee pain, improve knee function, and increase the quality of life. Thus, this combination can be used as a conservative treatment for KOA. However, due to the small number of high-quality articles and possible biases in our analysis, our conclusions need to be further verified in more and higher-quality studies.

A smelting multiple recrystallization strategy and its effects on the morphology, composition, and defects of CsPbBrI2 film were investigated. An optimal number (n = 2) of recrystallization cycles improved the crystallinity and phase purity, minimized the grain boundaries, and optimized the crystal structure, yielding a high-quality perovskite film with significantly reduced defects density. The corresponding photovoltaic devices exhibited a champion efficiency of 16.02% under AM 1.5 G illumination and presented an even higher indoor efficiency of 33.50% under an LED (2956 K, Pin: 334.41 μW/cm2). This recrystallization method offers a promising strategy for developing high-performance indoor and outdoor photovoltaics. Direct recrystallization in the cells was also explored to achieve enhanced stability and longer lifetime in humid conditions.

Wind power prediction (WPP) has an important impact on the security and reliability operation of power grid after a large amount of wind power integration into the system. There are two main challenges in WPP: 1) Both numerical weather prediction(NWP) data and wind power data contain abundant frequency information. If these data are directly inputted to the prediction model, the connection between different frequency bands is difficult to be mined. 2) Wind power has strong randomness and volatility, so the nonlinear relationship between input and output is difficult to be reflected by traditional prediction models. To overcome the challenge, a novel short-term WPP model based on wavelet feature arrangement and convolutional neural networks (CNN) is proposed in the paper. First, wavelet transform(WT) is applied to split the original NWP data and historical power data into multiple sets of different frequency components. Then, the features of different frequencies are arranged in various ways, named feature arrangement (FA), which are input into the CNN model for WPP, and finally, the prediction results are obtained. Two case studies demonstrated the effectiveness of the proposed novel WT-FA-CNN deep learning model for short-term WPP.

Dysbiosis of the human microbiome has long been reported to be closely associated with various cancers. Accumulating studies have shown that microbial dysbiosis can accelerate tumorigenesis through tumor-promoting inflammation, DNA damage, and inducing immune evasion. Differential composition of microbiome could be novel biomarkers for cancer detection or biomarkers of successful immunotherapy. More importantly, emerging evidence demonstrates that alterations of circulating microbiome DNA (cmDNA) could serve as promising noninvasive biomarkers for cancer detection. It has been reported that distinct circulating bacterial DNA could distinguish prostate cancer, lung cancer, and melanoma patients from healthy populations. Therefore, in this review, we summarized current literature on microbial biomarkers for cancer detection and unraveled the potential of cmDNA as a promising cancer detection tool.

Introduction The present study was aimed to evaluate the performance and safety of the Glunovo® real-time continuous glucose monitoring system (CGMS) in monitoring interstitial fluid glucose in adult participants with diabetes (at least 18 years old) using venous blood glucose as control. Methods This was a multicenter, self-controlled clinical trial, conducted in participants with diabetes from China, between March 2019 to October 2019. The CGMS was used by all the participants for a 14-day wear-in period. The real-time glucose values measured by Glunovo® CGMS were compared with venous blood glucose values measured by the Entwicklung, Konstruktion und Fertigung (EKF) blood glucose detector. The primary outcomes were the consistency rate of CGMS readings and venous blood glucose values (20/20% standard). Results A total of 78 participants (41 men, 37 women) and 156 CGMS sensors were included in the study. Among the included participants, 25 and 53 participants had type 1 and type 2 diabetes, respectively, with median age of 52.50 years (range 32–62 years). The overall agreement rate (20/20%) was 89.71% (95% CI 89.18–90.24%). It was observed that 99.08% (95% CI 98.91–99.24%) and 99.82% (95% CI 99.74–99.89%) of the measuring points fell within the A + B zones of the Clarke error grid analysis and Parkes/consensus error grid analysis, respectively. The mean absolute relative difference was 10.30% ± 4.86%. The probability of a glucose measurement falling within a range, when stratified by venous glucose measurements, ranged from 7.14% for 19.44–22.22 mmol/L to 79.21% for 4.44–6.67 mmol/L. There were 73 (41.24%) and 27 (57.45%) successful CGMS alarms for hypoglycemic and hyperglycemic events, respectively. Conclusion From the results, Glunovo® CGMS had excellent accuracy and limited clinical risk compared with venous blood glucose in the range of 2.2–22.2 mmol/L over 14 days. Supplementary Information The online version contains supplementary material available at 10.1007/s13300-021-01171-2.

Multiple Object Tracking (MOT) has attracted increasing interests in recent years, which plays a significant role in video analysis. MOT aims to track the specific targets as whole trajectories and locate the positions of the trajectory at different times. These trajectories are usually applied in Action Recognition, Anomaly Detection, Crowd Analysis and Multiple-Camera Tracking, etc. However, existing methods are still a challenge in complex scene. Generating false (impure, incomplete) tracklets directly affects the performance of subsequent tasks. Therefore, we propose a novel architecture, Siamese Bi-directional GRU, to construct Cleaving Network and Re-connection Network as trajectory post-processing. Cleaving Network is able to split the impure tracklets as several pure sub-tracklets, and Re-connection Network aims to re-connect the tracklets which belong to same person as whole trajectory. In addition, our methods are extended to Multiple-Camera Tracking, however, current methods rarely consider the spatial-temporal constraint, which increases redundant trajectory matching. Therefore, we present Position Projection Network (PPN) to convert trajectory position from local camera-coordinate to global world-coodrinate, which provides adequate and accurate temporal-spatial information for trajectory association. The proposed technique is evaluated over two widely used datasets MOT16 and Duke-MTMCT, and experiments demonstrate its superior effectiveness as compared with the state-of-the-arts.

Background Thalamic pain, a neuropathic pain syndrome, frequently occurs after stroke. This research aimed to investigate the effect of dexmedetomidine (DEX) on thalamic pain. Methods The cellular localization of the TLR4 protein was determined by immunostaining. The expression of Iba1, GFAP and protein associated with the TLR4/NF-κB/ERK1/2 pathway was measured by Western blotting. Continuous pain hypersensitivity was evaluated by behavioural tests. The results were analysed by one-way ANOVA, two-way ANOVA and Tukey’s post hoc test. Results The results demonstrated that DEX obviously alleviated thalamic pain induced by haemorrhage on the ipsilateral side and delayed the development of pain hypersensitivity. Furthermore, the expression levels of Iba1, GFAP and proteins associated with the TLR4/NF-κB/ERK1/2 signalling pathway were greatly increased in mice with thalamic pain, but these effects were reversed by DEX. Conclusion Our findings suggest that DEX alleviates the inflammatory response during thalamic pain through the TLR4/NF-κB/ERK1/2 signalling pathway and might be a potential therapeutic agent for thalamic pain.

Background With life span extending, breast cancer (BC) survivors may face the possibility of developing second primary cancer (SPC) and considerably shorten survivorship. However, little is known about multiple primary cancer (MPC) patients with nonmetastatic breast cancer as a first primary malignancy (BCFPM). Methods Here, we retrospectively analyzed data on cancer survivors with BCFPM diagnosed between 2010 and 2015 from the Surveillance, Epidemiology, and End Results (SEER) database. The prognostic factors for breast cancer‐specific survival (BCSS) were ascertained by the stepwise regression analysis and a competing risk model, and were integrated to the establishment of prognostic nomogram, of which the accuracy was measured by the calibration curve and the concordance index (C‐index). Results In total, 8616 patients were identified with 4.6% of 3‐year breast cancer‐ specific death (BCSD) and 8.6% of 5‐year BCSD. The most common SPC among BCFPM patients were female BC and lung cancer. Besides, the median latency time between BC and SPC was 22 months. At a ratio of 7:3, all patients were randomly categorized into a training cohort (n = 6032) and a validation cohort (n = 2584). By a proportional subdistribution hazards regression analysis, the following factors were considered to own independent prognostic abilities of BCSS: subtypes, grade, T classification, N classification, radiation, and sites of SPC. The nomogram could accurately predict 3‐year and 5‐year breast cancer‐associated survival of BCFPM patients with high internal and external validated C‐index, 0.715 (95% CI, 0.691–0.739), and 0.683 (95% CI, 0.642–0.724), respectively. Conclusions BC survivors remained a high risk of developing SPC and considerably shortened survival time. In this study, a favorable nomogram was constructed to as a prediction model for 3‐year and 5‐year BCSS of BCFPM patients, largely intending to prolong the life of these patients by assisting clinicians to make individualized follow‐up plans., A remarkable number of second primary cancers (SPC) occur in breast cancer survivors and constitute an emerging subgroup of tumors, with a shortage of overall understanding and normative management. Here, we gathered a mass of retrospective data with precise definition of SPC and further explored the clinical characteristics and prognostic predictors of these patients, thus effectively avoiding the deviation caused by small sample and SPC misclassification.