Enhanced reduction of graphene oxide via laser-dispersion coupling: Towards large-scale, low-defect graphene for crease-free heat-dissipating membranes in advanced flexible electronics.

The advancement of flexible electronics demands improved components, necessitating heat dissipation membranes (HDMs) to exhibit high thermal conductivity while maintaining structural integrity and performance stability even after extensive deformation. Herein, we have devised a laser-modulated reduction technique for graphene oxide (GO), enabling the fabrication of high-quality, large-scale, low-defect graphene, which yields high-performance HDMs after orderly deposition. The work underscores the crucial role of the laser wavelength and dispersion liquid's coupling intensity in influencing the morphology and properties of graphene. Optimal coupling effect and energy conversion are realized when a laser of 1064 nm wavelength irradiates a triethylene glycol (TEG)/N,N-Dimethylformamide (DMF) dispersion. This unique synergy generates high transient energy, which facilitates the deprotonation process and ensures a swift, comprehensive GO reduction. In contrast to conventional water-based laser reduction methods, the accelerated reaction magnifies the size of the graphene sheets by mitigating the ablation effect. After membrane construction with an ordered structure, the corresponding membrane exhibits a high thermal conductivity of 1632 W m-1 K-1, requiring only ∼1/10 of the total preparation time required by other reported methods. Remarkably, the resulting HDM demonstrates superior resilience against creasing and folding, maintaining excellent smoothness and negligible reduction in thermal conductivity after violent rubbing. The combination of exceptional flexibility and thermal conductivity in HDMs paves the way for long-term practical use in the flexible electronics industry.

[Research on Position Verification of Multi-Leaf Collimator (MLC) and Dose Verification Based on Electronic Portal Imaging Device].

Objective: A quality control (QC) system based on the electronic portal imaging device (EPID) system was used to realize the Multi-Leaf Collimator (MLC) position verification and dose verification functions on Primus and VenusX accelerators. Methods: The MLC positions were calculated by the maximum gradient method of gray values to evaluate the deviation. The dose of images acquired by EPID were reconstructed using the algorithm combining dose calibration and dose calculation. The dose data obtained by EPID and two-dimensional matrix (MapCheck/PTW) were compared with the dose calculated by Pinnacle/TiGRT TPS for γ passing rate analysis. Results: The position error of VenusX MLC was less than 1 mm. The position error of Primus MLC was significantly reduced after being recalibrated under the instructions of EPID. For the dose reconstructed by EPID, the average γ passing rates of Primus were 98.86% and 91.39% under the criteria of 3%/3 mm, 10% threshold and 2%/2 mm, 10% threshold, respectively. The average γ passing rates of VenusX were 98.49% and 91.11%, respectively. Conclusion: The EPID-based accelerator quality control system can improve the efficiency of accelerator quality control and reduce the workload of physicists.

Prognosis Prediction of Diffuse Large B-cell Lymphoma in 18F-FDG PET images Based on Multi-Deep-Learning Models.

Diffuse large B-cell lymphoma (DLBCL), a cancer of B cells, has been one of the most challenging and complicated diseases because of its considerable variation in clinical behavior, response to therapy, and prognosis. Radiomic features from medical images, such as PET images, have become one of the most valuable features for disease classification or prognosis prediction using learning-based methods. In this paper, a new flexible ensemble deep learning model is proposed for the prognosis prediction of the DLBCL in 18F-FDG PET images. This study proposes the multi-R-signature construction through selected pre-trained deep learning models for predicting progression-free survival (PFS) and overall survival (OS). The proposed method is trained and validated on two datasets from different imaging centers. Through analyzing and comparing the results, the prediction models, including Age, Ann abor stage, Bulky disease, SUVmax, TMTV, and multi-R-signature, achieve the almost best PFS prediction performance (C-index: 0.770, 95% CI: 0.705-0.834, with feature adding fusion method and C-index: 0.764, 95% CI: 0.695-0.832, with feature concatenate fusion method) and OS prediction (C-index: 0.770 (0.692-0.848) and 0.771 (0.694-0.849)) on the validation dataset. The developed multiparametric model could achieve accurate survival risk stratification of DLBCL patients. The outcomes of this study will be helpful for the early identification of high-risk DLBCL patients with refractory relapses and for guiding individualized treatment strategies.

Rubisco and sucrose synthesis and translocation are involved in the regulation of photosynthesis in wheat with different source-sink relationships.

Source-sink relationships influence photosynthesis. So far, the limiting factors for photosynthesis of wheat cultivars with different source-sink relationships have not been determined. We aimed to determine the variation patterns of photosynthetic characteristics of wheat cultivars with different source-sink relationships. In this study, two wheat cultivars with different source-sink relationships were selected for photosynthetic physiological analyses. The results showed that YM25 (source-limited cultivar) had higher photosynthetic efficiency compared to YM1 (sink-limited cultivar). This is mainly due to a stronger photochemical efficiency, electron transfer capacity, and Rubisco carboxylation capacity of YM25. YM25 accumulated less soluble carbohydrates in flag leaves than YM1. This is mainly due to the stronger sucrose synthesis and transport capacity of YM25 by presenting higher sucrose-related enzyme activities and gene expression. A PCA analysis showed that Rubisco was the main factor limiting the photosynthetic capacity of YM25. The soluble sugar accumulation in flag leaves and sink limitation decreased the photosynthetic activity of YM1. Increased N application improved source-sink relationships and increased grain yield and source leaf photosynthetic capacity in both two wheat cultivars. Taken together, our findings suggest that Rubisco and sucrose synthesis and translocation are involved in the regulation of photosynthesis of wheat cultivars with different source-sink relationships and that source and sink limitation effects should be considered in photosynthesis.

Diagnosis of benign and malignant peripheral lung lesions based on a feature model constructed by the random forest algorithm for grayscale and contrast-enhanced ultrasound.

Rationale and objectives: To construct a predictive model for benign and malignant peripheral pulmonary lesions (PPLs) using a random forest algorithm based on grayscale ultrasound and ultrasound contrast, and to evaluate its diagnostic value. Materials and methods: We selected 254 patients with PPLs detected using chest lung computed tomography between October 2021 and July 2023, including 161 malignant and 93 benign lesions. Relevant variables for judging benign and malignant PPLs were screened using logistic regression analysis. A model was constructed using the random forest algorithm, and the test set was verified. Correlations between these relevant variables and the diagnosis of benign and malignant PPLs were evaluated. Results: Age, lesion shape, size, angle between the lesion border and chest wall, boundary clarity, edge regularity, air bronchogram, vascular signs, enhancement patterns, enhancement intensity, homogeneity of enhancement, number of non-enhancing regions, non-enhancing region type, arrival time (AT) of the lesion, lesion-lung AT difference, AT difference ratio, and time to peak were the relevant variables for judging benign and malignant PPLs. Consequently, a model and receiver operating characteristic curve were constructed with an AUC of 0.92 and an accuracy of 88.2%. The test set results showed that the model had good predictive ability. The index with the highest correlation for judging benign and malignant PPLs was the AT difference ratio. Other important factors were lesion size, patient age, and lesion morphology. Conclusion: The random forest algorithm model constructed based on clinical data and ultrasound imaging features has clinical application value for predicting benign and malignant PPLs.

Hypoxia Reversion by Low-Immunogenic Ultra-Acid-Sensitive Comicelles of Protein-Polymer Conjugates Sensitizes Tumors to Photodynamic Therapy.

Hypoxia is characteristic of the tumor microenvironment, which is correlated with resistance to photodynamic therapy (PDT), radiotherapy, chemotherapy, and immunotherapy. Catalase is potentially useful to catalyze the conversion of endogenous H2O2 to O2 for hypoxia reversion. However, the efficient delivery of catalase into the hypoxia regions of tumors is a huge challenge. Here, we report the self-assembly of ultra-acid-sensitive polymer conjugates of catalase and albumin into nanomicelles that are responsive to the acidic tumor microenvironment. The immunogenicity of catalase is mitigated by the presence of albumin, which reduces the cross-linking of catalase with B cell receptors, resulting in improved pharmacokinetics. The ultra acid sensitivity of the nanomicelles makes it possible to efficiently escape the lysosomal degradation after endocytosis and permeate into the interior of tumors to reverse hypoxia in vitro and in vivo. In mice bearing triple-negative breast cancer, the nanomicelles loaded with a photosensitizer effectively accumulate and penetrate into the whole tumors to generate a sufficient amount of O2 to reverse hypoxia, leading to enhanced efficacy of PDT without detectable side effects. These findings provide a general strategy of self-assembly to design low-immunogenic ultra-acid-sensitive comicelles of protein-polymer conjugates to reverse tumor hypoxia, which sensitizes tumors to PDT.

A 4D-CBCT correction network based on contrastive learning for dose calculation in lung cancer.

OBJECTIVE: This study aimed to present a deep-learning network called contrastive learning-based cycle generative adversarial networks (CLCGAN) to mitigate streak artifacts and correct the CT value in four-dimensional cone beam computed tomography (4D-CBCT) for dose calculation in lung cancer patients. METHODS: 4D-CBCT and 4D computed tomography (CT) of 20 patients with locally advanced non-small cell lung cancer were used to paired train the deep-learning model. The lung tumors were located in the right upper lobe, right lower lobe, left upper lobe, and left lower lobe, or in the mediastinum. Additionally, five patients to create 4D synthetic computed tomography (sCT) for test. Using the 4D-CT as the ground truth, the quality of the 4D-sCT images was evaluated by quantitative and qualitative assessment methods. The correction of CT values was evaluated holistically and locally. To further validate the accuracy of the dose calculations, we compared the dose distributions and calculations of 4D-CBCT and 4D-sCT with those of 4D-CT. RESULTS: The structural similarity index measure (SSIM) and peak signal-to-noise ratio (PSNR) of the 4D-sCT increased from 87% and 22.31 dB to 98% and 29.15 dB, respectively. Compared with cycle consistent generative adversarial networks, CLCGAN enhanced SSIM and PSNR by 1.1% (p < 0.01) and 0.42% (p < 0.01). Furthermore, CLCGAN significantly decreased the absolute mean differences of CT value in lungs, bones, and soft tissues. The dose calculation results revealed a significant improvement in 4D-sCT compared to 4D-CBCT. CLCGAN was the most accurate in dose calculations for left lung (V5Gy), right lung (V5Gy), right lung (V20Gy), PTV (D98%), and spinal cord (D2%), with the relative dose difference were reduced by 6.84%, 3.84%, 1.46%, 0.86%, 3.32% compared to 4D-CBCT. CONCLUSIONS: Based on the satisfactory results obtained in terms of image quality, CT value measurement, it can be concluded that CLCGAN-based corrected 4D-CBCT can be utilized for dose calculation in lung cancer.

Simplified Modular Access to Enantiopure 1,2-Aminoalcohols via Ni-Electrocatalytic Decarboxylative Arylation.

Chiral aminoalcohols are omnipresent in bioactive compounds. Conventional strategies to access this motif involve multiple-step reactions to install the requisite functionalities stereoselectively using conventional polar bond analysis. This study reveals that a simple chiral oxazolidine-based carboxylic acid can be readily transformed to substituted chiral aminoalcohols with high stereochemical control by Ni-electrocatalytic decarboxylative arylation. This general, robust, and scalable coupling can be used to synthesize a variety of medicinally important compounds, avoiding protecting and functional group manipulations, thereby dramatically simplifying their preparation.

Brain functional connectivity alterations of Wernicke's area in individuals with autism spectrum conditions in multi-frequency bands: A mega-analysis.

Characterized by severe deficits in communication, most individuals with autism spectrum conditions (ASC) experience significant language dysfunctions, thereby impacting their overall quality of life. Wernicke's area, a classical and traditional brain region associated with language processing, plays a substantial role in the manifestation of language impairments. The current study carried out a mega-analysis to attain a comprehensive understanding of the neural mechanisms underpinning ASC, particularly in the context of language processing. The study employed the Autism Brain Image Data Exchange (ABIDE) dataset, which encompasses data from 443 typically developing (TD) individuals and 362 individuals with ASC. The objective was to detect abnormal functional connectivity (FC) between Wernicke's area and other language-related functional regions, and identify frequency-specific altered FC using Wernicke's area as the seed region in ASC. The findings revealed that increased FC in individuals with ASC has frequency-specific characteristics. Further, in the conventional frequency band (0.01-0.08 Hz), individuals with ASC exhibited increased FC between Wernicke's area and the right thalamus compared with TD individuals. In the slow-5 frequency band (0.01-0.027 Hz), increased FC values were observed in the left cerebellum Crus II and the right lenticular nucleus, pallidum. These results provide novel insights into the potential neural mechanisms underlying communication deficits in ASC from the perspective of language impairments.

Electroenzymatic tandem catalysis for the conversion of nitrate into ammonia.

A porous silver nanostructure-supported ionic liquid-modified chloroperoxidase nanohybrid was successfully used in electroenzymatic tandem catalysis to achieve an efficient, mild, and stable approach for the conversion of nitrate into ammonia.

A web-based tool for real-time adequacy assessment of kidney biopsies.

The escalating incidence of kidney biopsies providing insufficient tissue for diagnosis poses a dual challenge, straining the healthcare system and jeopardizing patients who may require rebiopsy or face the prospect of an inaccurate diagnosis due to an unsampled disease. Here, we introduce a web-based tool that can provide real-time, quantitative assessment of kidney biopsy adequacy directly from photographs taken with a smartphone camera. The software tool was developed using a deep learning-driven automated segmentation technique, trained on a dataset comprising nephropathologist-confirmed annotations of the kidney cortex on digital biopsy images. Our framework demonstrated favorable performance in segmenting the cortex via 5-fold cross-validation (Dice coefficient: 0.788±0.130) (n=100). Offering a bedside tool for kidney biopsy adequacy assessment has the potential to provide real-time guidance to the physicians performing medical kidney biopsies, reducing the necessity for re-biopsies. Our tool can be accessed through our web-based platform: http://www.biopsyadequacy.org.

A Model Combining Conventional Ultrasound Characteristics, Strain Elastography and Clinicopathological Features to Predict Ki-67 Expression in Small Breast Cancer.

To establish a predictive model incorporating conventional ultrasound, strain elastography and clinicopathological features for Ki-67 expression in small breast cancer (SBC) which defined as maximum diameter less than2 cm. In this retrospective study, 165 SBC patients from our hospital were allocated to a high Ki-67 group (n = 104) and a low Ki-67 group (n = 61). Multivariate regression analysis was performed to identify independent indicators for developing predictive models. The area under the receiver operating characteristic (AUC) curve was also determined to establish the diagnostic performance of different predictive models. The corresponding sensitivities and specificities of different models at the cutoff value were compared. Conventional ultrasound parameters (spiculated margin, absence of posterior shadowing and Adler grade 2-3), strain elastic scores and clinicopathological information (HER2 positive) were significantly correlated with high expression of Ki-67 in SBC (all p < .05). Model 2, which incorporated conventional ultrasound features and strain elastic scores, yielded good diagnostic performance (AUC = 0.774) with better sensitivity than model 1, which only incorporated ultrasound characteristics (78.85%vs. 55.77%, p = .000), with specificities of 77.05% and 62.30% (p = .035), respectively. Model 3, which incorporated conventional ultrasound, strain elastography and clinicopathological features, yielded better performance (AUC = 0.853) than model 1 (AUC = 0.694) and model 2 (AUC = 0.774), and the specificity was higher than model 1 (86.89% vs. 77.05%, p = .001). The predictive model combining conventional ultrasound, strain elastic scores and clinicopathological features could improve the predictive performance of Ki-67 expression in SBC.

Calibration-free quantitative phase imaging in multi-core fiber endoscopes using end-to-end deep learning.

Quantitative phase imaging (QPI) through multi-core fibers (MCFs) has been an emerging in vivo label-free endoscopic imaging modality with minimal invasiveness. However, the computational demands of conventional iterative phase retrieval algorithms have limited their real-time imaging potential. We demonstrate a learning-based MCF phase imaging method that significantly reduced the phase reconstruction time to 5.5 ms, enabling video-rate imaging at 181 fps. Moreover, we introduce an innovative optical system that automatically generated the first, to the best of our knowledge, open-source dataset tailored for MCF phase imaging, comprising 50,176 paired speckles and phase images. Our trained deep neural network (DNN) demonstrates a robust phase reconstruction performance in experiments with a mean fidelity of up to 99.8%. Such an efficient fiber phase imaging approach can broaden the applications of QPI in hard-to-reach areas.

AI-driven projection tomography with multicore fibre-optic cell rotation.

Optical tomography has emerged as a non-invasive imaging method, providing three-dimensional insights into subcellular structures and thereby enabling a deeper understanding of cellular functions, interactions, and processes. Conventional optical tomography methods are constrained by a limited illumination scanning range, leading to anisotropic resolution and incomplete imaging of cellular structures. To overcome this problem, we employ a compact multi-core fibre-optic cell rotator system that facilitates precise optical manipulation of cells within a microfluidic chip, achieving full-angle projection tomography with isotropic resolution. Moreover, we demonstrate an AI-driven tomographic reconstruction workflow, which can be a paradigm shift from conventional computational methods, often demanding manual processing, to a fully autonomous process. The performance of the proposed cell rotation tomography approach is validated through the three-dimensional reconstruction of cell phantoms and HL60 human cancer cells. The versatility of this learning-based tomographic reconstruction workflow paves the way for its broad application across diverse tomographic imaging modalities, including but not limited to flow cytometry tomography and acoustic rotation tomography. Therefore, this AI-driven approach can propel advancements in cell biology, aiding in the inception of pioneering therapeutics, and augmenting early-stage cancer diagnostics.

Porous NiMoO4 Nanosheet Films and a Device with Ultralarge Optical Modulation for Electrochromic Energy-Storage Applications.

Reducing building energy consumption, improving aesthetics, and improving occupant privacy as well as comfort by dynamically adjusting solar radiation are important application areas for electrochromic (EC) smart windows. However, the current transition metal oxides still cannot meet the requirements of neutral coloration and large optical modulation. We report NiMoO4 nanosheet films directly grown on fluorine-doped tin oxide glasses. The as-grown NiMoO4 film not only achieves neutral coloration from transparent to dark brown but also shows an ultralarge optical modulation (86.8% at 480 nm) and excellent cycling stability (99.4% retention of maximum optical modulation after 1500 cycles). Meanwhile, an EC device demonstrating good EC performance was constructed. These results will greatly promote the research and development of binary transition metal oxides for both EC and energy-storage applications, and NiMoO4 films may be an excellent candidate to replace NiO films as ion-storage layers in complementary EC devices with WO3 films as EC layers.

A Comparative Study on the Degradation Behaviors of Ferroelectric Gate GaN HEMT with PZT and PZT/Al2O3 Gate Stacks.

In this paper, the degradation behaviors of the ferroelectric gate Gallium nitride (GaN) high electron mobility transistor (HEMT) under positive gate bias stress are discussed. Devices with a gate dielectric that consists of pure Pb(Zr,Ti)O3 (PZT) and a composite PZT/Al2O3 bilayer are studied. Two different mechanisms, charge trapping and generation of traps, both contribute to the degradation. We have observed positive threshold voltage shift in both kinds of devices under positive gate bias stress. In the devices with a PZT gate oxide, we have found the degradation is owing to electron trapping in pre-existing oxide traps. However, the degradation is caused by electron trapping in pre-existing oxide traps and the generation of traps for the devices with a composite PZT/Al2O3 gate oxide. Owing to the large difference in dielectric constants between PZT and Al2O3, the strong electric field in the Al2O3 interlayer makes PZT/Al2O3 GaN HEMT easier to degrade. In addition, the ferroelectricity in PZT enhances the electric field in Al2O3 interlayer and leads to more severe degradation. According to this study, it is worth noting that the reliability problem of the ferroelectric gate GaN HEMT may be more severe than the conventional metal-insulator-semiconductor HEMT (MIS-HEMT).

Exploring the Mechanism of Immediate Analgesia Induced by Tuina Intervention on Minor Chronic Constriction Injury in Rats Using LC-MS.

Purpose: This study aimed to investigate changes in metabolomic expression in the spinal dorsal horn (SDH) and thalamus during a Tuina session, aiming to elucidate the mechanism of immediate analgesia. Methods: The rats were randomly divided into three groups: the Sham group, the Model group, and the Tuina group. A minor chronic constriction injury (minor CCI) model was established in both the Model group and the Tuina group. The therapeutic effect of Tuina was determined using the mechanical withdrawal threshold (MWT) and thermal withdrawal latency (TWL) tests. Differential metabolites of the SDH and thalamus were detected using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Bioinformatic analysis was performed using CV, PCA, Venn, and KEGG. Results: The therapeutic effect of MWT and TWL after instant Tuina intervention was significant. The therapeutic effect of Tuina instant was significantly better compared to the Model group. In the Veen analysis, it was found that Tuina instantly regulates 10 differential metabolites in the SDH and 5 differential metabolites in the thalamus. In the KEGG enrichment analysis, we found that differential metabolites were enriched in 43 pathways in the thalamus and 70 pathways in the SDH. Conclusion: Tuina therapy may have analgesic effects by metabolizing neurotransmitters such as 2-Picolinic Acid, 5-Hydroxy-Tryptophan Glutathione Betaine-aldehyde-chloride Leucine Lysine Methionine Sarcosine Succinic Acid Histidine Acetylcholine and 5-Hydroxyindoleacetic Acid through the cAMP pathway. It also affects pathways of neurodegeneration-multiple diseases, butanoate metabolism, tyrosine metabolism.

Discovery of 2,4-diarylaminopyrimidine derivatives bearing sulfonamide moiety as novel FAK inhibitors.

Two series of 2,4-diarylaminopyrimidine derivatives containing sulfonamide moiety were designed and synthesized for screening as inhibitors of focal adhesion kinase (FAK). Most compounds significantly inhibited the enzymatic activities of FAK, and the best compound was 7b (IC50 = 0.27 nM). A majority of aminoethyl sulfonamide derivatives could effectively inhibit the proliferation of human cancer cell lines (HCT116, A549, MDA-MB-231 and Hela) expressing high levels of FAK. Particularly, compounds 7b, 7c, and 7o exhibited more significant efficacy against all of four cancer cell lines within concentrations of 1.5 µM. Furthermore, these three compounds displayed higher selectivity of cancer cells over normal cells (SI value > 14), compared to the positive control TAE226 (SI value = 1.63). Interestingly, introduction of dithiocarbamate moiety to the aminoethyl sulfonamide derivatives can indeed improve the antiproliferative activities against A549 cells. Especially, compound 8d demonstrated most significant cytotoxicity activity against A549 cells with an IC50 value of 0.08 µM, which is 20-fold superior to parent compound 7k. Additionally, compound 7b, which display the best anti-FAK potency, can inhibit the clone formation and migration of HCT-116 cells, and cause cell cycle arrest at G2/M phase, inducing apoptosis by promoting ROS production. Overall, these results suggest that 7b is a valuable FAK inhibitor that deserves further optimization to improve its druggability.

Ultrasound-based radiomics nomogram for predicting axillary lymph node metastasis in early-stage breast cancer.

PURPOSE: We aimed at assessing the predictive ability of ultrasound-based radiomics combined with clinical characteristics for axillary lymph node (ALN) status in early-stage breast cancer patients and to compare performance in different peritumoral regions. MATERIALS AND METHODS: A total of 755 patients (527 in the primary cohort and 228 in the external validation cohort) were enrolled in this study. Ultrasound images for all patients were acquired and radiomics analysis performed for intratumoral and different peritumoral regions. The MRMR and LASSO regression analyses were performed on extracted features from the primary cohort to construct a radiomics signature formula combined with clinical characteristics. Pearson's coefficient and the variance inflation factor (VIF) were performed to check the correlation and the multicollinearity among the final predictors. The best performing model was selected to develop a nomogram, which was established by performing binary logistic regression and acquiring cut-off values based on the corresponding nomogram scores of the masses. RESULTS: Among all the radiomics models, the "Mass + Margin3mm" model exhibited the best performance. The areas under the curves (AUC) of the nomogram in the primary and external validation cohorts were 0.906 (95% confidence intervals [CI] 0.882-0.930) and 0.922 (95% CI 0.894-0.960), respectively. They both showed good calibrations. The nomogram exhibited a good ability to discriminate between positive and negative lymph nodes (AUC: 0.853 (95% CI 0.816-0.889) in primary cohort, 0.870 (95% CI 0.818-0.922) in validation cohort), and between low-volume and high-volume lymph nodes (AUC: 0.832 (95% CI 0.781-0.884) in primary cohort, 0.911 (95% CI 0.858-0.964) in validation cohort). CONCLUSIONS: The established nomogram is a prospective clinical prediction tool for non-invasive assessment of ALN status. It has the ability to enhance the accuracy of early-stage breast cancer treatment.

A Superlong-Acting Growth Hormone-Polypeptide Fusion for Growth Hormone Deficiency Treatment.

Recombinant human growth hormone (rhGH) is clinically used to treat growth hormone deficiency (GHD). However, daily administration of rhGH is required due to its poor stability and short blood circulation, which causes pains and burdens as well as inconvenience to patients. In this study, a method for genetically fusing rhGH to a thermosensitive polymer of elastin-like polypeptide (ELP) is reported, using which the rhGH-ELP thermosensitive fusion protein can be purified by the thermosensitivity of ELP instead of chromatography. The ELP fusion not only drastically improves the stability of rhGH, but also enables the in situ formation of a sustained-release depot of rhGH-ELP upon subcutaneous (SC) injection, which exhibits gentle release with a platform-to-trough fluctuation in blood and a very long circulatory half-life of 594.6 h. In contrast, rhGH exhibits a peak-to-trough fluctuation in blood with a very short circulatory half-life of 0.7 h. As a result, a single subcutaneous injection of rhGH-ELP can consecutively promote the linear growth of rats and the development of major tissues and organs over 3 weeks without obvious side effects, whereas rhGH is required to be injected daily to achieve similar therapeutic results.