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Abstract Targeted alpha (α) therapy (TAT) is an emerging therapeutic strategy for cancer treatment. To evaluate the safety and efficacy of targeted α‐therapy, the biodistribution and internal radiation dose of α‐emitting radionuclides should be determined. In vivo imaging of these radionuclides often involves the detection of gamma rays, X‐rays, and positrons generated during their complex decay processes. This review aims to classify the α‐emitting radionuclides (astatine‐211, actinium‐225, radium‐223, bismuth‐212, bismuth‐213, thorium‐227, and terbium‐149) according to their imageable signals. Additionally, this study summarizes various imaging modalities, including gamma camera imaging, single‐photon emission computed tomography, positron emission tomography, Compton imaging, bremsstrahlung imaging, and Cerenkov luminescence imaging, which hold potential for imaging α‐emitting radionuclides, to explore their biomedical applications in qualitative nuclide tracing and diagnosis, quantifying pharmacokinetics, and assessing prognosis and response to therapy.

Abstract Background Currently, the synthesis pathway of metal nuclide-labeled radiopharmaceuticals is mainly divided into two steps: first, connecting the chelator with the target molecule, and second, labeling the metal nuclide to the chelator. However, the second step of the reaction to label the metal nuclide requires high temperature (90–100 °C), which tends to denature and inactivate the target molecule, leading to loss of biological activities, especially the targeting ability. A feasible solution may be the click chemistry labeling method, which consists of reacting a metal nuclide with a chelating agent to generate an intermediate and then synthesizing a radiopharmaceutical agent via the click chemistry intermediate and the target molecule-alkyne compound. In this study, through the click chemistry of 177Lu-DOTA-N3 with prostate-specific membrane antigen (PSMA)-alkyne compound, 177Lu-labeled PSMA-targeted molecular probe was synthesized and evaluated for its potential to be cleared from the bloodstream and rapidly distributed to tissues and organs, achieving a high target/non-target ratio. 177Lu-PSMA-617 was utilized as an analogue for comparison in terms of synthesizing efficiency and PSMA-targeting ability. Results A novel 177Lu-labeled PSMA radioligand was successfully synthesized through the click chemistry of 177Lu-DOTA-N3 with PSMA-alkyne compound, and abbreviated as 177Lu-DOTA-CC-PSMA, achieving a radiochemical yield of 77.07% ± 0.03% (n = 6) and a radiochemical purity of 97.62% ± 1.49% (n = 6) when purified by SepPak C18 column. Notably, 177Lu-DOTA-CC-PSMA was characterized as a hydrophilic compound that exhibited stability at room temperature and commendable pharmacokinetic properties, such as the superior uptake (19.75 ± 3.02%ID/g at 0.5 h) and retention (9.14 ± 3.16%ID/g at 24 h) within xenografts of 22Rv1 tumor-bearing mice. SPECT/CT imaging indicated that radioactivity in both kidneys and bladder was essentially eliminated after 24 h, while 177Lu-DOTA-CC-PSMA was further enriched and retained in PSMA-expressing tumors, resulting in the high target/non-target ratio. Conclusion This study demonstrated the potential of click chemistry to unify the synthesis of metal radiopharmaceuticals, and 177Lu-DOTA-CC-PSMA was found for rapid clearance and appropriate chemical stability as a PSMA-targeted radioligand.

Background: Hepatocellular carcinoma (HCC) is among the most prevalent digestive system malignancies and is associated with a poor prognosis. Necroptosis, a form of regulated death mediated by death receptors, exhibits characteristics of both necrosis and apoptosis. Long non-coding RNAs (lncRNAs) have been identified as crucial regulators in tumor necroptosis. This study aims to identify the necroptosis-related lncRNAs (np-lncRNA) in HCC and investigate their relationships with prognosis. Method: The RNA-sequencing data, along with clinicopathological and survival information of HCC patients were sourced from The Cancer Genome Atlas (TCGA) database. The np-lncRNAs were analyzed to assess their potential in predicting HCC prognosis. Prognostic signatures related to necroptosis were constructed using stepwise multivariate Cox regression analysis. The prognosis of patients was compared using Kaplan-Meier (KM) analysis. The accuracy of the prognostic signature was evaluated using Receiver operating characteristic (ROC) analysis and decision curve analysis (DCA). Quantitative real-time polymerase chain reaction(qPCR) was employed to validate the lncRNAs expression levels of lncRNAs among samples from an independent cohort. Results: The np-lncRNAs ZFPM2-AS1, AC099850.3, BACE1-AS, KDM4A-AS1 and MKLN1-AS were identified as potential prognostic biomarkers. The prognostic signature constructed from these np-lncRNAs achieved an Area Under the Curve (AUC) of 0.773. Based on the risk score derived from the signature, patients were divided into two groups, with the high-risk group exhibiting poorer overall survival. Gene Set Enrichment Analysis (GSEA) revealed significantly different between the low risk and high risk groups in tumor-related pathways (such as mTOR, MAPK and p53 signaling pathways) and immune-related functions (like T cell receptor signaling pathway and natural killer cell mediated cytotoxicity). The increased expression of np-lncRNAs was confirmed in another independent HCC cohort. Conclusions: This signature offers a dependable method for forecasting the prognosis of HCC patients. Our findings indicate a subset of np-lncRNA biomarkers that could be utilized for prognosis prediction and personalized treatment strategies of HCC patients.

Abstract Despite the array of mammalian transgene switches available for regulating therapeutic protein expression in response to small molecules or physical stimuli, issues remain, including cytotoxicity of chemical inducers and limited biocompatibility of physical cues. This study introduces gene switches driven by short peptides comprising eight or fewer amino acid residues. Utilizing a competence regulator (ComR) and sigma factor X‐inducing peptide (XIP) from Streptococcus vestibularis as the receptor and inducer, respectively, this study develops two strategies for a peptide‐activated transgene control system. The first strategy involves fusing ComR with a transactivation domain and utilizes ComR‐dependent synthetic promoters to drive expression of the gene‐of‐interest, activated by XIP, thereby confirming its membrane penetrability and intracellular functionality. The second strategy features an orthogonal synthetic receptor exposing ComR extracellularly (ComREXTRA), greatly increasing sensitivity with exceptional responsiveness to short peptides. In a proof‐of‐concept study, peptides are administered to type‐1 diabetic mice with microencapsulated engineered human cells expressing ComREXTRA for control of insulin expression, restoring normoglycemia. It is envisioned that this system will encourage the development of short peptide drugs and promote the introduction of non‐toxic, orthogonal, and highly biocompatible personalized biopharmaceuticals for gene‐ and cell‐based therapies.

BackgroundHypoparathyroidism is the most common complication for patients who undergo total thyroidectomy (TT) with bilateral central lymph node dissection (BCLND). The objective of this retrospective study was to investigate the relationship between parathyroid autotransplantation (PA) and postoperative hypoparathyroidism.Materials and MethodsFour hundred and sixty-five patients with papillary thyroid carcinoma (PTC) who underwent TT with BCLND (including prophylactic and therapeutic BCLND) by the same surgeon were enrolled in this retrospective study. They were divided into five groups based on the number of PAs. Group 0 was defined as no PA, while Group 1, 2, 3, and 4 were considered as 1, 2, 3, and 4 PAs during TT with BCLND, respectively.ResultsTransient and permanent hypoparathyroidism occurred in 83 (17.8%) and 2 (0.4%) patients who underwent TT and BCLND, respectively. The incidence of transient hypoparathyroidism increased gradually with an increase in the number of PAs. Compared with the previous group, Groups 2 and 3 had significantly more cases of transient hypoparathyroidism (p=0.03 and p=0.04, respectively). All cases of permanent hypoparathyroidism occurred in the patients without PA. Compared with Group 0, there were more removed central lymph nodes (RCLNs) in patients with one PA. Furthermore, Group 2 had more metastatic central lymph nodes(MCLNs) and RCLNs than Group 1.The number of PAs was the only identified risk factor for transient hypoparathyroidism after the multivariate logistic regression analysis. The median parathyroid hormone level recovered to the normal range within 1 month after surgery.ConclusionWith an increasing number of PAs, the possibility of transient hypoparathyroidism also increases in patients with PTC who undergo TT and BCLND. Considering the rapid recovery of transient hypoparathyroidism in 1 month, two PAs during TT and BCLND could be a good choice, leading to an increase in the central lymph node yield and no permanent hypoparathyroidism. However, this conclusion should be validated in future multicenter prospective studies.

Abstract China, as a significant global consumer of chemical fertilizers and a leading producer of rice, faces challenges associated with low fertilizer efficiency and fewer utilization options of rice husks. The development of rice husk biochar‐based fertilizers (RHBF) offers a strategic solution to address these issues. In this study, diverse biochar fertilizer production techniques were used to develop four types of fertilizers: blended RHBF, soaked RHBF, high‐pressure soaked RHBF, and pure rice husk biochar coated fertilizer. The nutrients slow‐releasing performance of these four RHBF were compared by hydrostatic and soil column intermittent leaching methods. Effects of their application on rice growth, yield, and cadmium reduction potential were analyzed and compared by the pot trial. Results demonstrated that nutrients of the four RHBF were generally released slower in the soil compared with the conventional compound fertilizer (CK). The slow nutrient release effect was more pronounced under high‐pressure soaked RHBF. Notably, in the soil column leaching experiment, the cumulative leaching rates of nitrogen and K2O for RHBF3 (12.0% and 13.9%) were greatly lower than those of CK (42.3% and 51.3%). Moreover, the application of RHBF induced a marked enhancement in the nutrient use efficiency, grain yield, harvest index, and photosynthetic characteristics compared to CK. The average agronomic efficiency of P2O5 for the four RHBF increased by 102.8% compared with CK, while the average grain yield of the four RHBF increased by 20.6%. In addition, RHBF showed a significant reduction in Cd mobilization by an average of 80.1% compared to CK. This study offers a promising model for enhancing the comprehensive performance of RHBF and optimizing traditional fertilizer application practices.

Abstract Synthetic biology aims to engineer transgene switches for precise therapeutic protein control in cell‐based gene therapies. However, off‐the‐shelf trigger‐inducible gene circuits are usually switched on by single or structurally similar molecules. This study presents a mammalian gene‐switch platform that controls therapeutic gene expression by a wide range of molecules generating low, non‐toxic levels of reactive oxygen species (ROS). In this system, KEAP1 (Kelch‐like ECH‐associated protein 1) serves as ROS sensor, regulating the translocation of NRF2 (nuclear factor erythroid 2‐related factor 2) to the nucleus, where NRF2 binds to antioxidant response elements (ARE) to activate the expression of a gene of interest. It is found that a promoter containing eight‐tandem ARE repeats is highly sensitive to the low ROS levels generated by the soluble and volatile molecules, which include food preservatives, food additives, pharmaceuticals, and signal transduction inducers. In a proof‐of‐concept study, it is shown that many of these compounds can independently trigger microencapsulated engineered cells to produce sufficient insulin to restore normoglycemia in experimental type‐1 diabetic mice. It is believed that this system greatly extends the variety of small‐molecule inducers available to drive therapeutic gene switches.

Abstract Viral proteases and clinically safe inhibitors were employed to build integrated compact regulators of protein activity (iCROP) for post-translational regulation of functional proteins by tunable proteolytic activity. In the absence of inhibitor, the co-localized/fused protease cleaves a target peptide sequence introduced in an exposed loop of the protein of interest, irreversibly fragmenting the protein structure and destroying its functionality. We selected three proteases and demonstrated the versatility of the iCROP framework by validating it to regulate the functional activity of ten different proteins. iCROP switches can be delivered either as mRNA or DNA, and provide rapid actuation kinetics with large induction ratios, while remaining strongly suppressed in the off state without inhibitor. iCROPs for effectors of the NF-κB and NFAT signaling pathways were assembled and confirmed to enable precise activation/inhibition of downstream events in response to protease inhibitors. In lipopolysaccharide-treated mice, iCROP-sr-IκBα suppressed cytokine release (“cytokine storm”) by rescuing the activity of IκBα, which suppresses NF-κB signaling. We also constructed compact inducible CRISPR-(d)Cas9 variants and showed that iCROP-Cas9-mediated knockout of the PCSK9 gene in the liver lowered blood LDL-cholesterol levels in mice. iCROP-based protein switches will facilitate protein-level regulation in basic research and translational applications.

Reusable launch vehicles need to face complex and diverse environments during flight. The design of rocket recovery control law based on traditional deep reinforcement learning (DRL) makes it difficult to obtain a set of network architectures that can adapt to multiple scenarios and multi-parameter uncertainties, and the performance of deep reinforcement learning algorithm depends on manual trial and error of hyperparameters. To solve this problem, this paper proposes a self-learning control method for launch vehicle recovery based on neural architecture search (NAS), which decouples deep network structure search and reinforcement learning hyperparameter optimization. First, using network architecture search technology based on a multi-objective hybrid particle swarm optimization algorithm, the proximal policy optimization algorithm of deep network architecture is automatically designed, and the search space is lightweight design in the process. Secondly, in order to further improve the landing accuracy of the launch vehicle, the Bayesian optimization (BO) method is used to automatically optimize the hyperparameters of reinforcement learning, and the control law of the landing phase in the recovery process of the launch vehicle is obtained through training. Finally, the algorithm is transplanted to the rocket intelligent learning embedded platform for comparative testing to verify its online deployment capability. The simulation results show that the proposed method can satisfy the landing accuracy of the launch vehicle recovery mission, and the control effect is basically the same as the landing accuracy of the trained rocket model under the untrained condition of model parameter deviation and wind field interference, which verifies the generalization of the proposed method.

During aerial combat, when an aircraft is facing an infrared air-to-air missile strike, infrared baiting technology is an important means of penetration, and the strategy of effective delivery of infrared bait is critical. To address this issue, this study proposes an improved deep deterministic policy gradient (DDPG) algorithm-based intelligent bait-dropping control method. Firstly, by modeling the relative motion between aircraft, bait, and incoming missiles, the Markov decision process of aircraft-bait-missile infrared effect was constructed with visual distance and line of sight angle as states. Then, the DDPG algorithm was improved by means of pre-training and classification sampling. Significantly, the infrared bait-dropping decision network was trained through interaction with the environment and iterative learning, which led to the development of the bait-dropping strategy. Finally, the corresponding environment was transferred to the Nvidia Jetson TX2 embedded platform for comparative testing. The simulation results showed that the convergence speed of this method was 46.3% faster than the traditional DDPG algorithm. More importantly, it was able to generate an effective bait-throwing strategy, enabling the aircraft to successfully evade the attack of the incoming missile. The strategy instruction generation time is only about 2.5 ms, giving it the ability to make online decisions.

Marginal lands, such as those with saline soils, have potential as alternative resources for cultivating dedicated biomass crops used in the production of renewable energy and chemicals. Optimum utilization of marginal lands can not only alleviate the competition for arable land use with primary food crops, but also contribute to bioenergy products and soil improvement. Miscanthus sacchariflorus and M. lutarioriparius are prominent perennial plants suitable for sustainable bioenergy production in saline soils. However, their responses to salt stress remain largely unexplored. In this study, we utilized 318 genotypes of M. sacchariflorus and M. lutarioriparius to assess their salt tolerance levels under 150 mM NaCl using 14 traits, and subsequently established a mini-core elite collection for salt tolerance. Our results revealed substantial variation in salt tolerance among the evaluated genotypes. Salt-tolerant genotypes exhibited significantly lower Na+ content, and K+ content was positively correlated with Na+ content. Interestingly, a few genotypes with higher Na+ levels in shoots showed improved shoot growth characteristics. This observation suggests that M. sacchariflorus and M. lutarioriparius adapt to salt stress by regulating ion homeostasis, primarily through enhanced K+ uptake, shoot Na+ exclusion, and Na+ sequestration in shoot vacuoles. To evaluate salt tolerance comprehensively, we developed an assessment value (D value) based on the membership function values of the 14 traits. We identified three highly salt-tolerant, 50 salt-tolerant, 127 moderately salt-tolerant, 117 salt-sensitive, and 21 highly salt-sensitive genotypes at the seedling stage by employing the D value. A mathematical evaluation model for salt tolerance was established for M. sacchariflorus and M. lutarioriparius at the seedling stage. Notably, the mini-core collection containing 64 genotypes developed using the Core Hunter algorithm effectively represented the overall variability of the entire collection. This mini-core collection serves as a valuable gene pool for future in-depth investigations of salt tolerance mechanisms in Miscanthus.

Using contaminated land to grow lignocellulosic crops can deliver biomass and, in the long term, improve soil quality. Biostimulants and microorganisms are nowadays an innovative approach to define appropriate phytomanagement strategies to promote plant growth and metal uptake. This study evaluated biostimulants and mycorrhizae application on biomass production and phytoextraction potential of four lignocellulosic crops grown under two metal-contaminated soils. Two greenhouse pot trials were setup to evaluate two annual species (sorghum, hemp) in Italy and two perennial ones (miscanthus, switchgrass) in China, under mycorrhizae (M), root (B2) and foliar (B1) biostimulants treatments, based on humic substances and protein hydrolysates, respectively, applied both alone and in combination (MB1, MB2). MB2 increased the shoot dry weight (DW) yield in hemp (1.9 times more), sorghum (3.6 times more) and miscanthus (tripled) with additional positive effects on sorghum and miscanthus Zn and Cd accumulation, respectively, but no effects on hemp metal accumulation. No treatment promoted switchgrass shoot DW, but M enhanced Cd and Cr shoot concentrations (+84%, 1.6 times more, respectively) and the phytoextraction efficiency. Root biostimulants and mycorrhizae were demonstrated to be more efficient inputs than foliar biostimulants to enhance plant development and productivity in order to design effective phytomanagement strategies in metal-contaminated soil.

The pretreatment of lignocellulosic biomass such as Miscanthus grown on marginal agricultural land is very challenging and requires severe conditions to fractionate cell wall polymers for further valorization. The current study aimed to determine organic acid-based mild conditions to pretreat contrasting lignocellulosic Miscanthus genotypes for the efficient fractionation of cell wall components, with special focus on hemicellulose extraction. In doing so, five Miscanthus genotypes were subjected to four different acid treatments (sulfuric acid, oxalic acid, malonic acid, and citric acid) in a vertical high-pressure steam sterilizer. The results demonstrated that, among the organic acids, oxalic acid was identified as the most effective pretreatment solvent for hemicellulose separation, whereas citric acid yielded the highest amount of galacturonic acid, varying from 15 to 17 mg mL−1 across genotypes. One best performing genotype was selected for the enzymatic hydrolysis. Overall, M. floridulus genotypes exhibited the optimal quality traits for efficient bioconversion with second best in terms of ethanol production potential.

The identification of slag inclusion defects in welds is of the utmost importance in guaranteeing the integrity, safety, and prolonged service life of welded structures. Most research focuses on different kinds of weld defects, but branch research on categories of slag inclusion material is limited and critical for safeguarding the quality of engineering and the well-being of personnel. To address this issue, we design a simulated method using ultrasonic testing to identify the inclusion of material categories in austenitic stainless steel. It is based on a simulated experiment in a water environment, and six categories of cubic specimens, including four metallic and two non-metallic materials, are selected to simulate the slag materials of the inclusion defects. Variational mode decomposition optimized by particle swarm optimization is employed for ultrasonic signals denoising. Moreover, the phase spectrum of the denoised signal is utilized to extract the phase characteristic of the echo signal from the water–slag specimen interface. The experimental results show that our method has the characteristics of appropriate decomposition and good denoising performance. Compared with famous signal denoising algorithms, the proposed method extracted the lowest number of intrinsic mode functions from the echo signal with the highest signal-to-noise ratio and lowest normalized cross-correlation among all of the comparative algorithms in signal denoising of weld slag inclusion defects. Finally, the phase spectrum can ascertain whether the slag inclusion is a thicker or thinner medium compared with the weld base material based on the half-wave loss existing or not in the echo signal phase.

Miscanthus spp. has been regarded as a promising industrial plant for the sustainable production of bio-based materials. To assess its potential for microcrystalline cellulose (MCC) and cellulose nanocrystals (CNCs) production, 50 representative clones of M. sinensis and M. floridulus were selected from a nationwide collection showcasing the extensive diversity of germplasm resources. Descriptive analysis indicates that the dry biomass weight of M. floridulus is advantageous whereas M. sinensis demonstrates higher MCC and CNCs yields as well as a smaller CNCs particle size. Correlation analyses indicated that MCC yield is solely influenced by the cellulose content whereas the yield of CNCs is affected by both the cellulose content and CrI. Comparative analyses of the chemical composition, physical features (degree of polymerization, crystalline index, particle size distribution and zeta potential), and scanning electron microscopy indicated that the MCC and CNCs extracted from M. sinensis and M. floridulus exhibited remarkable stability and quality. Additionally, the CNCs derived from M. sinensis and M. floridulus exhibited a distinctive ball-shaped structure. Notably, machine learning has demonstrated its efficacy and effectiveness in the high-throughput screening of large populations of Miscanthus spp. for predicting the yield of MCC and CNCs. Our results have also laid the theoretical foundation for the exploration, cultivation, and genetic breeding of M. sinensis and M. floridulus germplasm resources with the purpose of MCC and CNCs preparation.