3D-printed PCL framework assembling ECM-inspired multi-layer mineralized GO-Col-HAp microscaffold for in situ mandibular bone regeneration.

BACKGROUND: In recent years, natural bone extracellular matrix (ECM)-inspired materials have found widespread application as scaffolds for bone tissue engineering. However, the challenge of creating scaffolds that mimic natural bone ECM's mechanical strength and hierarchical nano-micro-macro structures remains. The purposes of this study were to introduce an innovative bone ECM-inspired scaffold that integrates a 3D-printed framework with hydroxyapatite (HAp) mineralized graphene oxide-collagen (GO-Col) microscaffolds and find its application in the repair of mandibular bone defects. METHODS: Initially, a 3D-printed polycaprolactone (PCL) scaffold was designed with cubic disks and square pores to mimic the macrostructure of bone ECM. Subsequently, we developed multi-layer mineralized GO-Col-HAp microscaffolds (MLM GCH) to simulate natural bone ECM's nano- and microstructural features. Systematic in vitro and in vivo experiments were introduced to evaluate the ECM-inspired structure of the scaffold and to explore its effect on cell proliferation and its ability to repair rat bone defects. RESULTS: The resultant MLM GCH/PCL composite scaffolds exhibited robust mechanical strength and ample assembly space. Moreover, the ECM-inspired MLM GCH microscaffolds displayed favorable attributes such as water absorption and retention and demonstrated promising cell adsorption, proliferation, and osteogenic differentiation in vitro. The MLM GCH/PCL composite scaffolds exhibited successful bone regeneration within mandibular bone defects in vivo. CONCLUSIONS: This study presents a well-conceived strategy for fabricating ECM-inspired scaffolds by integrating 3D-printed PCL frameworks with multilayer mineralized porous microscaffolds, enhancing cell proliferation, osteogenic differentiation, and bone regeneration. This construction approach holds the potential for extension to various other biomaterial types.

Development and validation of a model for predicting upstage in minimally invasive lung adenocarcinoma in Chinese people.

BACKGROUND: Sublobar resection for ground-glass opacity became a recommend surgery choice supported by the JCOG0804/JCOG0802/JCOG1211 results. Sublobar resection includes segmentectomy and wedge resection, wedge resection is suitable for non-invasive lesions, but in clinical practice, when pathologists are uncertain about the intraoperative frozen diagnosis of invasive lesions, difficulty in choosing the appropriate operation occurs. The purpose of this study was to analyze how to select invasive lesions with clinic-pathological characters. METHODS: A retrospective study was conducted on 134 cases of pulmonary nodules diagnosed with minimally invasive adenocarcinoma by intraoperative freezing examination. The patients were divided into two groups according to intraoperative frozen results: the minimally invasive adenocarcinoma group and the at least minimally invasive adenocarcinoma group. A variety of clinical features were collected. Chi-square tests and multiple regression logistic analysis were used to screen out independent risk factors related to pathological upstage, and then ROC curves were established. In addition, an independent validation set included 1164 cases was collected. RESULTS: Independent risk factors related to pathological upstage were CT value, maximum tumor diameter, and frozen result of AL-MIA. The AUC of diagnostic mode was 71.1% [95%CI: 60.8-81.3%]. The independent validation included 1164 patients, 417 (35.8%) patients had paraffin-based pathology of invasive adenocarcinoma. The AUC of diagnostic mode was 75.7% [95%CI: 72.9-78.4%]. CONCLUSIONS: The intraoperative frozen diagnosis was AL-MIA, maximum tumor diameter larger than 15 mm and CT value is more than - 450Hu, highly suggesting that the lung GGO was invasive adenocarcinoma which represent a higher risk to recurrence. For these patients, sublobectomy would be insufficient, lobectomy or complementary treatment is encouraged.

Deep drug-target binding affinity prediction with multiple attention blocks.

Drug-target interaction (DTI) prediction has drawn increasing interest due to its substantial position in the drug discovery process. Many studies have introduced computational models to treat DTI prediction as a regression task, which directly predict the binding affinity of drug-target pairs. However, existing studies (i) ignore the essential correlations between atoms when encoding drug compounds and (ii) model the interaction of drug-target pairs simply by concatenation. Based on those observations, in this study, we propose an end-to-end model with multiple attention blocks to predict the binding affinity scores of drug-target pairs. Our proposed model offers the abilities to (i) encode the correlations between atoms by a relation-aware self-attention block and (ii) model the interaction of drug representations and target representations by the multi-head attention block. Experimental results of DTI prediction on two benchmark datasets show our approach outperforms existing methods, which are benefit from the correlation information encoded by the relation-aware self-attention block and the interaction information extracted by the multi-head attention block. Moreover, we conduct the experiments on the effects of max relative position length and find out the best max relative position length value $k \in \{3, 5\}$. Furthermore, we apply our model to predict the binding affinity of Corona Virus Disease 2019 (COVID-19)-related genome sequences and $3137$ FDA-approved drugs.

One-Step Reverse-Transcription Loop-Mediated Isothermal Amplification (RT-LAMP) Assay for the Detection of Canna Yellow Streak Virus.

Canna yellow streak virus (CaYSV) is a potyvirus that causes severe damage to the ornamental plant canna in the United Kingdom and Brazil. Here, we identified CaYSV in China by isolating total RNA from an infected plant, amplifying the virus genome segments, and cloning and sequencing the amplicons. After assembly, the full-length genome of the virus was obtained and uploaded to the NCBI database. Phylogenetic analysis results showed that the Guizhou isolate (OL546222) was most closely related to the KS isolate (MG545919.1). Virus detection is essential for virus disease control but the subclinical infection of CaYSV on canna in its early development increases the difficulty of CaYSV diagnosis. The goal of this study was to develop an efficient method for detection of CaYSV. We designed the primers, optimized the reaction conditions, and finally established a one-step reverse-transcription loop-mediated isothermal amplification (RT-LAMP) method. The product of RT-LAMP can be analyzed by both agarose gel electrophoresis and visible color change. The established one-step RT-LAMP assay showed high specificity and sensitivity in detecting CaYSV. This RT-LAMP method was also applied in analysis of 61 field samples collected from Guizhou and Jiangsu Provinces. The results showed that the infection rates of CaYSV on canna samples from these two provinces were very high (63 and 96% respectively).

Multi-scaled self-attention for drug-target interaction prediction based on multi-granularity representation.

BACKGROUND: Drug-target interaction (DTI) prediction plays a crucial role in drug discovery. Although the advanced deep learning has shown promising results in predicting DTIs, it still needs improvements in two aspects: (1) encoding method, in which the existing encoding method, character encoding, overlooks chemical textual information of atoms with multiple characters and chemical functional groups; as well as (2) the architecture of deep model, which should focus on multiple chemical patterns in drug and target representations. RESULTS: In this paper, we propose a multi-granularity multi-scaled self-attention (SAN) model by alleviating the above problems. Specifically, in process of encoding, we investigate a segmentation method for drug and protein sequences and then label the segmented groups as the multi-granularity representations. Moreover, in order to enhance the various local patterns in these multi-granularity representations, a multi-scaled SAN is built and exploited to generate deep representations of drugs and targets. Finally, our proposed model predicts DTIs based on the fusion of these deep representations. Our proposed model is evaluated on two benchmark datasets, KIBA and Davis. The experimental results reveal that our proposed model yields better prediction accuracy than strong baseline models. CONCLUSION: Our proposed multi-granularity encoding method and multi-scaled SAN model improve DTI prediction by encoding the chemical textual information of drugs and targets and extracting their various local patterns, respectively.

Artificial intelligence for stepwise diagnosis and monitoring of COVID-19.

BACKGROUND: Main challenges for COVID-19 include the lack of a rapid diagnostic test, a suitable tool to monitor and predict a patient's clinical course and an efficient way for data sharing among multicenters. We thus developed a novel artificial intelligence system based on deep learning (DL) and federated learning (FL) for the diagnosis, monitoring, and prediction of a patient's clinical course. METHODS: CT imaging derived from 6 different multicenter cohorts were used for stepwise diagnostic algorithm to diagnose COVID-19, with or without clinical data. Patients with more than 3 consecutive CT images were trained for the monitoring algorithm. FL has been applied for decentralized refinement of independently built DL models. RESULTS: A total of 1,552,988 CT slices from 4804 patients were used. The model can diagnose COVID-19 based on CT alone with the AUC being 0.98 (95% CI 0.97-0.99), and outperforms the radiologist's assessment. We have also successfully tested the incorporation of the DL diagnostic model with the FL framework. Its auto-segmentation analyses co-related well with those by radiologists and achieved a high Dice's coefficient of 0.77. It can produce a predictive curve of a patient's clinical course if serial CT assessments are available. INTERPRETATION: The system has high consistency in diagnosing COVID-19 based on CT, with or without clinical data. Alternatively, it can be implemented on a FL platform, which would potentially encourage the data sharing in the future. It also can produce an objective predictive curve of a patient's clinical course for visualization. KEY POINTS: • CoviDet could diagnose COVID-19 based on chest CT with high consistency; this outperformed the radiologist's assessment. Its auto-segmentation analyses co-related well with those by radiologists and could potentially monitor and predict a patient's clinical course if serial CT assessments are available. It can be integrated into the federated learning framework. • CoviDet can be used as an adjunct to aid clinicians with the CT diagnosis of COVID-19 and can potentially be used for disease monitoring; federated learning can potentially open opportunities for global collaboration.

Correction: High-efficiency and high-fidelity ssDNA circularisation via the pairing of five 3'-terminal bases to assist LR-LAMP for the genotyping of single-nucleotide polymorphisms.

Correction for 'High-efficiency and high-fidelity ssDNA circularisation via the pairing of five 3'-terminal bases to assist LR-LAMP for the genotyping of single-nucleotide polymorphisms' by Taiwen Li et al., Analyst, 2022, https://doi.org/10.1039/d2an01042a.

High-efficiency and high-fidelity ssDNA circularisation via the pairing of five 3'-terminal bases to assist LR-LAMP for the genotyping of single-nucleotide polymorphisms.

The poor fidelity of T4 DNA ligase has always limited the simple detection of single-nucleotide polymorphisms (SNPs) and is only applicable to some special SNP types. This study developed a highly sensitive and specific detection method for SNPs based on high-fidelity single-stranded circularisation. It used T4 DNA ligase and rolling circle amplification (RCA) plus loop-mediated isothermal amplification (LAMP). Surprisingly, the cyclisation stage's efficiency greatly improved. The ligation fidelity was almost perfect via the unique pairing pattern between a long-paired base at the 5' terminus and only five bases at the 3' terminus on linear single-stranded DNA (l-DNA). Subsequently, LR-LAMP was performed and combined with the circularisation step for the simple detection of SNPs. The results showed that even 100 aM targets could be detected correctly and that a mutation rate of 0.1% or even 0.01% could be analysed via naked-eye visualisation or fluorescence detection, respectively. In addition, genomic DNA samples were used to evaluate the method, which indicated that it could effectively distinguish the SNPs of RPA190-T1145A in Phytophthora infestans. This strategy may play an important role in both circularisation of single-stranded DNA and detecting arbitrary SNPs.

Identification and genome analysis of a tomato zonate spot virus isolate from Bidens pilosa.

Bidens pilosa is a weed species that invades crop areas in tropical and subtropical regions. To date, only two potyviruses have been reported to infect B. pilosa. Here, we report the complete genome sequence of a tomato zonate spot tospovirus (TZSV) isolate from Bidens named TZSV-Bidens. The tripartite RNA of the TZSV-Bidens genome contains L, M, and S segments that are 8912, 4724, and 2997 nt in length, respectively. The genome contains five open reading frames (ORFs), with 92.23-95.01% amino acid sequence identity to the TZSV-YN isolate. Phylogenetic analysis based on amino acid sequences of members of the family Tospoviridae showed that TZSV-Bidens was grouped into a well-supported Eurasian cluster. The intergenic regions (IGRs) of the M and S RNAs are among the most variable regions and are far shorter than those of the TZSV-YN reference genome.

First Report of Pestalotiopsis lushanensis Causing Brown Leaf Spot on Sarcandra glabra in China.

Sarcandra glabra is a species of Chloranthaceae family and this family grow in the southern part of China, Japan, and Southeastern Asia (Li et al. 2019). It is a kind of precious Chinese herbal medicine, which occupies an important position in traditional Chinese herbal medicine. It plays an effective role in the treatment of cancer, rheumatism, pneumonia, digestive tract inflammations, traumatic injuries and fractures, anti-virus, anti-bacterial, antioxidant, etc. (Li et al. 2019; Zheng et al. 2003; Zhou et al. 2013). Since June 2020, we discovered a serious leaf disease in the S. glabra planting base of Shibing County (108.12E 27.03N), in Guizhou Province, with an incidence rate of 60% and yield losses of 40%. Initially, the symptoms developed as small specks where spots were purple with a dark brown halo margin, and round or oval. In later stages, the spots gradually expanded and became dry, whole severe leaf loss. To identify the pathogen, we collected the diseased leaves from S. glabra fields in Shibing County. Small tissue pieces from the edges of lesions were disinfected in 75% ethyl alcohol for 30 s and 1% hypochlorite for 1 min, rinsed five times in sterile water, plated on potato dextrose agar (PDA), and incubated at 28°C in lighted incubator for 3 days. Fungal colonies were consistently isolated and transferred to PDA for morphological characterization (Fang et al. 2007). Pathogenicity tests of the novel isolate HGUP CSH-2 were conducted by spraying spore suspensions with a concentration of 1.6×108 conidia/ml on surface-disinfected (70% ethyl alcohol, 30 s) leaves, while sterile distilled water was used as the control. Plants with inoculated leaves (three per treatment) were placed in lighted growth chambers at 28°C for 5 days and watered as needed (Light to dark ratio 1:1, RH=90%). Symptoms on inoculated leaves were similar to those described previously in the field. The same pathogenic fungus was re-isolated from the infected leaves but not from the non-inoculated leaves. Colonies on PDA attaining 70 mm diam after 7 d at 28°C, with pale honey-colored, sparse aerial mycelia on the surface with black, gregarious conidiomata. Conidiogenous cell discrete or integrated, ampulliform, clavate or subcylindrical, hyaline, smooth-walled, wide at base. Conidia fusoid, ellipsoid, straight to slightly curved, 4-septate, slightly constricted at septa, 22.26-27.17×6.9-8.22 µm (av.±SD: 24.68±1.57×7.68±0.38 µm; n=30). According to the colony and conidia characteristics, the isolate was initially identified as Pestalotiopsis spp. (Liu et al. 2017). The pathogen was confirmed by amplification and sequencing of the internal transcribed spacer region (ITS) gene, the translation elongation factor-1 (TEF1) gene and the ß-tubulin (TUB2) gene (Liu et al. 2017) using ITS1/ITS4, Bt2a/T1 and EF1-526F/1567R primers, respectively. The sequences of the PCR products were deposited in GenBank with accession numbers MT919215 (ITS), MT939300 (TUB2) and MT939299 (TEF1). BLAST results of the obtained sequences of the ITS, TUB2 and TEF1 genes revealed 97.16% (479/493 nucleotides), 99.56% (675/678 nucleotides) and 99.89% (890/891 nucleotides) homology with those of Pestalotiopsis lushanensis in GenBank (MG726538, KY464157 and KX895223). Maximum Likelihood method was used for phylogenetic analysis. The result showed that HGUP CSH-2 was together with P. lushanensis with a support rate of 100%. According to the morphological characteristics and molecular phylogenetic analysis, the pathogen was identified as P. lushanensis. So far as we know, our research is the first report of brown leaf spot of S. glabra caused by P. lushanensis in China. Thus, identification of P. lushanensis for this disease is important for the advancement of effective prevention and control practises as future perspectives.

A case report of multicentric reticulohistiocytosis with atypical cutaneous presentation.

Multicentric reticulohistiocytosis (MRH) is a rare systemic disorder characterized by histiocytic hyperplasia that mainly involves the skin, mucous membranes, and joints. The typical clinical features include papules, nodules, and arthritis. MRH lesions are relatively extensive but small and scattered. Joint inflammation is characterized by diffuse symmetric polyarthritis as the first symptom, which can be severe and disabling due to destructive joint changes. MRH is easily misdiagnosed in clinical practice. Here, we report the case of an elderly male patient who presented with polyarticular pain in the hip and interphalangeal joints as the first manifestation, followed by the development of large, isolated, bulging skin nodules, which are atypical MRH lesions. This is rare in all MRH case reports, and we made the correct diagnosis by combining skin histopathology, immunohistochemistry, and other clinical examinations. We performed surgical treatment on the local skin lesions of this patient. This case suggests that clinicians should actively correlate the condition and accurately diagnose MRH when encountering atypical skin changes or other diseases as the first symptom and explore the mechanisms of MRH and other clinical manifestations.

A middle lobe sparing sleeve resection versus bilobectomy for right lower central non-small cell lung cancer: a retrospective propensity score matched cohort study.

OBJECTIVES: The right lower sleeve lobectomy is a rarely performed major lung resection.This study aims to evaluate the safety and effectiveness of this procedure by comparing to right lower bilobectomy in non-small cell lung cancer patients. METHODS: We retrospectively reviewed a prospective database of non-small cell lung cancer patients who underwent right lower sleeve lobectomy (group S) or right lower bilobectomy (group B) from January 2014 to January 2020 in Shanghai Pulmonary Hospital. Propensity score matching method was applied to balance confounders between the two groups, resulting in 41 matched pairs.The analysis was performed to compare perioperative outcomes, long-term survival, and postoperative pulmonary volume between the two groups. RESULTS: No significant differences in the characteristics were observed between the two matched groups.Major postoperative complications developed in 31.7% of the patients in group B and 12.1% of the patients in group S (P = 0.032).Intervention rate for surgical residual cavity in group B is significantly higher than those patients in group S(21.9%vs7.3%,p = 0.037).The postoperative right lateral and overall lung volume in group S were both significantly larger than that in group B (P = 0.026,P = 0.001,respectively). CONCLUSIONS: Compared to bi-lobectomy, a middle lobe sparing sleeve resection obtains a less prevalence of major complications, smaller postoperative residual air space and similar long-term survival for selected central right lower NSCLC patients.

Robust deep learning from incomplete annotation for accurate lung nodule detection.

Deep learning plays a significant role in the detection of pulmonary nodules in low-dose computed tomography (LDCT) scans, contributing to the diagnosis and treatment of lung cancer. Nevertheless, its effectiveness often relies on the availability of extensive, meticulously annotated dataset. In this paper, we explore the utilization of an incompletely annotated dataset for pulmonary nodules detection and introduce the FULFIL (Forecasting Uncompleted Labels For Inexpensive Lung nodule detection) algorithm as an innovative approach. By instructing annotators to label only the nodules they are most confident about, without requiring complete coverage, we can substantially reduce annotation costs. Nevertheless, this approach results in an incompletely annotated dataset, which presents challenges when training deep learning models. Within the FULFIL algorithm, we employ Graph Convolution Network (GCN) to discover the relationships between annotated and unannotated nodules for self-adaptively completing the annotation. Meanwhile, a teacher-student framework is employed for self-adaptive learning using the completed annotation dataset. Furthermore, we have designed a Dual-Views loss to leverage different data perspectives, aiding the model in acquiring robust features and enhancing generalization. We carried out experiments using the LUng Nodule Analysis (LUNA) dataset, achieving a sensitivity of 0.574 at a False positives per scan (FPs/scan) of 0.125 with only 10% instance-level annotations for nodules. This performance outperformed comparative methods by 7.00%. Experimental comparisons were conducted to evaluate the performance of our model and human experts on test dataset. The results demonstrate that our model can achieve a comparable level of performance to that of human experts. The comprehensive experimental results demonstrate that FULFIL can effectively leverage an incomplete pulmonary nodule dataset to develop a robust deep learning model, making it a promising tool for assisting in lung nodule detection.

Construction and antibacterial activities of walnut green husk polysaccharide based silver nanoparticles (AgNPs).

In this paper, the size-controllable nano­silver particles (AgNPs) were synthesized from walnut green husk polysaccharide, and its cytotoxicity and antibacterial activity were evaluated. Firstly, acidic polysaccharide WGHP2 was extracted from walnut green husk, and then the silver ion in AgNO3 was reduced in WGHP2 aqueous solution using NaBH4, so as to synthesize the nano­silver composite. The nano­silver composite was characterized by transmission electron microscope, Fourier infrared spectroscopy, ultraviolet-visible spectrometer, scanning electron microscope, inductively coupled plasma mass spectrometry and X-ray photoelectron spectroscopy. The results show that AgNPs stabilized by WGHP2 are mainly regular spheres with an average particle size distribution of 15.04-19.23 nm. The particle size distribution and morphology of AgNPs changed with the concentration of silver precursor, which is related to the dispersion of silver precursor in polysaccharide aqueous solution and the formation of AgO coordination bond between silver precursor and polysaccharide molecules. These coordination bonds changed the ability of nanoparticles to produce and release Ag+, and thus regulated their antibacterial activity and cytotoxicity, as evidenced by the experimental result of the cytotoxicity of the nano­silver particle against PC12 cells and the bacteriostatic effect on E.coli and S.aureus. Conclusively, WGHP2-Ag has good stability, antibacterial activity and low cytotoxicity.

Tailored gelatin methacryloyl-based hydrogel with near-infrared responsive delivery of Qiai essential oils boosting reactive oxygen species scavenging, antimicrobial, and anti-inflammatory activities for diabetic wound healing.

The management of diabetic wounds poses a substantial economic and medical burden for diabetic patients. Oxidative stress and persistent bacterial infections are considered to be the primary factors. Qiai essential oil (QEO) exhibits various pharmacological characteristics, including inflammatory-reducing, antibacterial, and antioxidant properties. Nevertheless, the hydrophobic nature and propensity for explosive release of this substance present constraints on its potential for future applications. Here, we developed a stimulus-responsive hydrogel to overcome the multiple limitations of QEO-based wound dressings. The QEO was encapsulated within graphene oxide (GO) through repeated extrusion using an extruder. Subsequently, QEO@GO nanoparticles were incorporated into a Gelatin-methacryloyl (GelMA) hydrogel. The QEO@GO-GelMA hydrogel demonstrated controlled release ablation, photothermal antibacterial effects, and contact ablation against two representative bacterial strains. It effectively reduced reactive oxygen species (ROS) generation, promoted angiogenesis, and decreased levels of the pro-inflammatory cytokine interleukin-6 (IL-6), thereby accelerating the healing process of diabetic wounds. In addition, in vitro and in vivo tests provided further evidence of the favorable biocompatibility of this multifunctional hydrogel dressing. Overall, the QEO@GO-GelMA hydrogel provides numerous benefits, encompassing antimicrobial properties, ROS-scavenging abilities, anti-inflammatory effects, and the capacity to expedite diabetic wound healing. These attributes make it an optimal choice for diabetic wound management.

Enhanced physiochemical, antibacterial, and hemostatic performance of collagen-quaternized chitosan-graphene oxide sponges for promoting infectious wound healing.

Bacteria-infected wound healing has attracted widespread attention in biomedical engineering. Wound dressing is a potential strategy for repairing infectious wounds. However, the development of wound dressing with appropriate physiochemical, antibacterial, and hemostatic properties, remains challenging. Hence, there is a motivation to develop new synthetic dressings to improve bacteria-infected wound healing. Here, we fabricate a biocompatible sponge through the covalent crosslinking of collagen (Col), quaternized chitosan (QCS), and graphene oxide (GO). The resulting Col-QCS-GO sponge shows an elastic modulus of 1.93-fold higher than Col sponge due to enhanced crosslinking degree by GO incorporation. Moreover, the fabricated Col-QCS-GO sponge shows favorable porosity (84.30 ± 3.12 %), water absorption / retention (2658.0 ± 113.4 % / 1114.0 ± 65.7 %), and hemostasis capacities (blood loss <50.0 mg). Furthermore, the antibacterial property of the Col-QCS-GO sponge under near-infrared (NIR) irradiation is significantly enhanced (the inhibition rates are 99.9 % for S. aureus and 99.9 % for E. coli) due to the inherent antibacterial properties of QCS and the photothermal antibacterial capabilities of GO. Finally, the Col-QCS-GO+NIR sponge exhibits the lowest percentage of wound area (9.05 ± 1.42 %) at day 14 compared to the control group (31.61 ± 1.76 %). This study provides new insights for developing innovative sponges for bacteria-infected wound healing.

Efficacy and safety of ultrasound-guided thermal ablation of graves' disease: a retrospective cohort study.

BACKGROUND: Ultrasound-guided thermal ablation (TA) has emerged as a robust therapeutic approach for treating solid tumors in multiple organs, including the thyroid. Yet, its efficacy and safety profile in the management of Graves' Disease (GD) remains to be definitively established. METHODS: A retrospective study was conducted on 50 GD patients treated with TA between October 2017 and December 2021. Key metrics like thyroid volume, volume reduction rate (VRR), thyroid hormones, and basal metabolic rate (BMR) were evaluated using paired Wilcoxon tests. RESULTS: The intervention of ultrasound-guided TA yielded a statistically significant diminution in total thyroid volume across all postoperative follow-up intervals-1, 3, 6, and 12 months-relative to pre-intervention baselines (p < 0.001). The median VRR observed at these time points were 17.5%, 26.5%, 34.4%, and 39.8%, respectively. Euthyroid status was corroborated in 96% of patients at the one-year follow-up milestone. Transient tachycardia and dysphonia were observed in three patients, while a solitary case of skin numbness was noted. Crucially, no instances of enduring injury to the recurrent laryngeal nerve (RLN) were documented. CONCLUSIONS: Our investigation substantiates ultrasound-guided TA as a pragmatic, well-tolerated, and safe therapeutic modality for GD. It effectively improves symptoms of hyperthyroidism, engenders a substantial reduction in thyroid volume, and restores thyroid hormone and BMR to physiological levels. Given its favorable safety profile, enhanced cosmetic outcomes, and minimally invasive nature, ultrasound-guided TA is a compelling alternative to thyroidectomy for GD patients.

Nonstructural protein P7-2 encoded by Rice black-streaked dwarf virus interacts with SKP1, a core subunit of SCF ubiquitin ligase.

BACKGROUND: Rice black-streaked dwarf virus (RBSDV), a member of the genus Fijivirus within the family Reoviridae, causes severe damage to cereal crops in South East Asia. The protein P7-2, encoded by the second open reading frame of segment S7, is conserved among most plant-infecting fijiviruses, but its function is still obscure. RESULTS: In this study, P7-2 was used as bait in two-hybrid screens of a cDNA library expressing Zea mays proteins. It was found that there is a strong interaction between P7-2 and Z. mays SKP1 (SKP1Maize), a core subunit of the multicomponent SCF (SKP1/Cullin1/F-box/Rbx1) E3 ubiquitin ligase. The interaction was then confirmed in leaf epidermal cells of Nicotiana benthamiana by bimolecular fluorescence complementation assay. Further investigations indicated that P7-2 also interacts with SKP1 proteins from other plants, including Arabidopsis thaliana, N. benthamiana,Oryza sativa and Saccharum sinense. The C-terminal fragment of SKP1Maize (residues 97-176) and the middle fragment of P7-2 (residues 79-214) are necessary to sustain the interaction, while the C-terminal putative α-helix domain spanning residues 214-295 of P7-2 greatly facilitates the interaction. Agrobacterium-mediated transient suppression assay showed that P7-2 has no obvious activity to suppress local RNA silencing. CONCLUSIONS: Taken together, our results indicated that RBSDV P7-2 can interact with SKP1 proteins from different plants. This is the first report linking a Fijivirus protein to a component of the ubiquitin proteasome system. P7-2 might be a potential F-box protein encoded by RBSDV and involved in the plant-virus interaction through ubiquitination pathway.

VO2max (VO2peak) in elite athletes under high-intensity interval training: A meta-analysis.

Consensus is lacking regarding whether high-intensity interval training (HIIT) effectively improves VO2max (VO2peak) in elite athletes (Athlete must be involved in regular competition at the national level). This meta-analysis compared the effects of HIIT and conventional training methods (continuous training, repeated-sprint training, high volume low-intensity training, high-intensity continuous running, sprint-interval training, moderate-intensity continuous training)on VO2max in elite athletes. Nine studies were included, comprising 176 elite athletes (80 female). Compared to that with conventional training, VO2max was significantly increased after HIIT (overall: 0.58 [0.30, 0.87], I2 = 0.49, P = 0.03; males: 0.41 [0.06, 0.76], I2 = 0%, P = 0.89). VO2max had positive training effects when the HIIT recovery period had an interval time ≥2 min (0.44 [0.03, 0.84], I2 = 0%, P = 0.99) and recovery phase intensity ≤40% (0.38 [0.05, 0.71], I2 = 0%, P = 0.96). Thus, HIIT shows superiority over conventional training methods in improving VO2max, promoting aerobic capacity, in elite athletes.

Trigger-activated autonomous DNA machine for amplified liver cancer biomarker microRNA21 imaging.

MicroRNA-21 (miRNA-21) is a kind of RNA that exists in biological fluids such as blood, urine and saliva. It has over expression in liver cancer and has different expression in different stages of cancer. However, due to the characteristics of small base number, short length, low abundance and easy degradation of miRNA-21, the detection of miRNA-21 is a challenging subject. Visualization, sensitive, specific and stable detection of tumor suppressor or oncogene microRNAs (miRNAs) remains challenging and is highly significant for clinical diagnostics. To solve this problem, we have developed a target-triggered hybridization assembly DNA machine for intracellular miRNA imaging based on strand displacement amplification (SDA) and branched hybridization chain reaction (B-HCR). In this approach, the target miRNA could hybridize with the template probe to trigger the SDA, resulting in the formation of nicked fragments (NFs) that hybridized with hairpin probe1 (HP1). The opened HP1 could hybridize with hairpin probe2 (HP2), leading to the self-assembly of hyperbranched DNA nanostructures through B-HCR. As expected, the newly developed method exhibits a detection limit down to 11.3 pM miRNA-21 and achieves high selectivity toward miRNA-21 against other interfering miRNAs. Due to its superior sensitivity and selectivity, our method can be further used to detect miRNA-21 in human serum samples. By taking advantage of intelligent design, the proposed method was also used for image miRNA-21 expression levels in different cell lines. This method shows a broad application in clinical diagnosis.