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.

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.

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.

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.

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.

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.

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.

Graphene Oxide Functionalized Gelatin Methacryloyl Microgel for Enhanced Biomimetic Mineralization and in situ Bone Repair.

Introduction: The formation of bone-like apatite (Ap) on natural polymers through biomimetic mineralization using simulated body fluid (SBF) can improve osteoconductivity and biocompatibility, while lowering immunological rejection. Nonetheless, the coating efficiency of the bone-like Ap layer on natural polymers requires improvement. Carbonyls (-COOH) and hydroxyls (-OH) are abundant in graphene oxide (GO), which may offer more active sites for biomimetic mineralization and promote the proliferation of rat bone marrow stromal cells (BMSCs). Methods: In this study, gelatin methacryloyl (GelMA) microgels were infused with GO (0, 0.5, 1, and 2 mg/mL) and embedded into microgels in SBF for 1, 7, and 14 days. Systematic in vitro and in vivo experiments were performed to evaluate the structure of the microgel and its effect on cell proliferation and ability to repair bone defects in rats. Results: The resulting GO-GelMA-Ap microgels displayed a porous, interconnected structure with uniformly coated surfaces in bone-like Ap, and the Ca/P ratio of the 1 mg/mL GO-GelMA-Ap group was comparable to that of natural bone tissue. Moreover, the 1 mg/mL GO-GelMA-Ap group exhibited a greater Ap abundance, enhanced proliferation of BMSCs in vitro and increased bone formation in vivo compared to the GelMA-Ap group. Discussion: Overall, this study offers a novel method for incorporating GO into microgels for bone tissue engineering to promote biomimetic mineralization.

Pan-mediastinal neoplasm diagnosis via nationwide federated learning: a multicentre cohort study.

BACKGROUND: Mediastinal neoplasms are typical thoracic diseases with increasing incidence in the general global population and can lead to poor prognosis. In clinical practice, the mediastinum's complex anatomic structures and intertype confusion among different mediastinal neoplasm pathologies severely hinder accurate diagnosis. To solve these difficulties, we organised a multicentre national collaboration on the basis of privacy-secured federated learning and developed CAIMEN, an efficient chest CT-based artificial intelligence (AI) mediastinal neoplasm diagnosis system. METHODS: In this multicentre cohort study, 7825 mediastinal neoplasm cases and 796 normal controls were collected from 24 centres in China to develop CAIMEN. We further enhanced CAIMEN with several novel algorithms in a multiview, knowledge-transferred, multilevel decision-making pattern. CAIMEN was tested by internal (929 cases at 15 centres), external (1216 cases at five centres and a real-world cohort of 11 162 cases), and human-AI (60 positive cases from four centres and radiologists from 15 institutions) test sets to evaluate its detection, segmentation, and classification performance. FINDINGS: In the external test experiments, the area under the receiver operating characteristic curve for detecting mediastinal neoplasms of CAIMEN was 0·973 (95% CI 0·969-0·977). In the real-world cohort, CAIMEN detected 13 false-negative cases confirmed by radiologists. The dice score for segmenting mediastinal neoplasms of CAIMEN was 0·765 (0·738-0·792). The mediastinal neoplasm classification top-1 and top-3 accuracy of CAIMEN were 0·523 (0·497-0·554) and 0·799 (0·778-0·822), respectively. In the human-AI test experiments, CAIMEN outperformed clinicians with top-1 and top-3 accuracy of 0·500 (0·383-0·633) and 0·800 (0·700-0·900), respectively. Meanwhile, with assistance from the computer aided diagnosis software based on CAIMEN, the 46 clinicians improved their average top-1 accuracy by 19·1% (0·345-0·411) and top-3 accuracy by 13·0% (0·545-0·616). INTERPRETATION: For mediastinal neoplasms, CAIMEN can produce high diagnostic accuracy and assist the diagnosis of human experts, showing its potential for clinical practice. FUNDING: National Key R&D Program of China, National Natural Science Foundation of China, and Beijing Natural Science Foundation.

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.

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.

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).

Development and validation of nomogram prognostic model for early-stage T1-2N0M0 small cell lung cancer: A population-based analysis.

Background: Survival outcomes of early-stage T1-2N0M0 small cell lung cancer (SCLC) patients differ widely, and the existing Veterans Administration Lung Study Group (VALSG) or TNM staging system is inefficient at predicting individual prognoses. In our study, we developed and validated nomograms for individually predicting overall survival (OS) and lung cancer-specific survival (LCSS) in this special subset of patients. Methods: Data on patients diagnosed with T1-2N0M0 SCLC between 2000 and 2015 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. All enrolled patients were split into a training cohort and a validation cohort according to the year of diagnosis. Using multivariable Cox regression, significant prognostic factors were identified and integrated to develop nomograms for 1-, 3-, and 5-year OS and LCSS prediction. The prognostic performance of our new model was measured by the concordance index (C-index) and calibration curve. We compared our latest model and the 8th AJCC staging system using decision curve analyses (DCA). Kaplan-Meier survival analyses were applied to test the application of the risk stratification system. Results: A total of 1,147 patients diagnosed from 2000 to 2011 were assigned to the training cohort, and 498 cases that were diagnosed from 2012 to 2015 comprised the validation cohort. Age, surgery, lymph node removal (LNR), and chemotherapy were independent predictors of LCSS. The variables of sex, age, surgery, LNR, and chemotherapy were identified as independent predictors of OS. The above-mentioned prognostic factors were entered into the nomogram construction of OS and LCSS. The C-index of this model in the training cohort was 0.663, 0.702, 0.733, and 0.658, 0.702, 0.733 for predicting 1-, 3-, and 5-year OS and LCSS, respectively. Additionally, in the validation cohort, there were 0.706, 0.707, 0.718 and 0.712, 0.691, 0.692. The calibration curve showed accepted prediction accuracy between nomogram-predicted survival and actual observed survival, regardless of OS or LCSS. In addition, there were significant distinctions in the survival curves of OS and LCSS between different risk groups stratified by prognostic scores. Compared with the 8th AJCC staging system, our new model also improved net benefits. Conclusions: We developed and validated novel nomograms for individual prediction of OS and LCSS, integrating the characteristics of patients and tumors. The model showed superior reliability and may help clinicians make treatment strategies and survival predictions for early-stage T1-2N0M0 SCLC patients.

Bioengineered polyester nanoparticles for the synergistic treatment of androgenic alopecia via the suppression of 5α-reductase and knockdown of androgen receptor.

Androgenic alopecia (AGA) is a common disease that negatively affects patients' physical and mental health. AGA can be treated with drugs that improve the perifollicular microenvironment, such as 5α-reductase inhibitors (e.g., dutasteride [DUT]), androgen receptor blockers, and minoxidil. However, the efficacy of these treatments is limited. Therefore, this study aimed to show that nanoparticles are effective as stable carriers with high curative benefits and little adverse effects. The in vitro study showed that PLGA-DUT/siAR@DPCM NPs could deliver both DUT and siAR to dermal papilla cells. They could successfully suppress 5α-reductase and knock down androgen receptor, respectively, and thereby promote cell proliferation. In the in vivo study, PLGA-DUT/siAR@DPCM NPs showed a significant therapeutic effect in an AGA mouse model. They successfully penetrated the stratum corneum and showed a clear targeting effect on hair follicles and surrounding tissues. PLGA-DUT/siAR@DPCM NPs could enable the targeted delivery of DUT and siAR through percutaneous penetration, enhancing phagocytosis and decreasing adverse effects. Thus, they have great potential in the clinical treatment of AGA.

Molecular characterization of a novel partitivirus isolated from Rhizoctonia solani.

Rhizoctonia solani is a widely distributed plant pathogen that can damage many crops. Here, we identified a novel mycovirus tentatively named Rhizoctonia solani partitivirus 433 (RsPV433) from an R. solani (AG-3) strain which caused tobacco target spot disease on flue-cured tobacco. RsPV433 was consisted of two dsRNA segments with lengths of 2450 and 2273 bp, which encoded an RNA-dependent RNA polymerase and a coat protein, respectively. BLASTP results of RsPV433 showed that the closest relative of RsPV433 was Sarcosphaera coronaria partitivirus (QLC36830.1), with an identity of 60.85% on the RdRp amino sequence. Phylogenetic analysis indicated that RsPV433 belonged to the Betapartitivirus genus in the Partitiviridae family. The virus transmission experiment revealed that RsPV433 can be transmitted horizontally. We further tested the biological effect of RsPV433 on R. solani strains and found that the RsPV433-infected R. solani strain grew slower than the RsPV433-free strain on the PDA medium and RsPV433 seemed to have no obvious impact on the lesion inducing ability of R. solani.

Bacillus velezensis Strain GUMT319 Reshapes Soil Microbiome Biodiversity and Increases Grape Yields.

Bacillus velezensis strain GUMT319 is a rhizobacteria biocontrol agent that can control tobacco black shank disease. We took GUMT319 as a biological fertilizer on Vitis vinifera L. The test group was treated with GUMT319 for one year and the control group had a water treatment. Yields of GUMT319-treated grape groups were significantly increased compared to the controls. The average length and width of single grape fruit, weight of 100 grape fruits, the sugar/acid ratio, and the content of vitamin C were all increased in the GUMT319-treated grape group. The pH of the soil was higher and the contents of alkaline hydrolyzable nitrogen and available potassium were significantly lower in the GUMT319-treated groups than the controls. The soil microbial community composition was evaluated by 16S rDNA high-throughput sequencing, and the Shannon index and Simpson index all showed that soil microbes were more abundant in the GUMT319-treated group. These results indicate that GUMT319 is not only a biocontrol agent, but also a plant growth-promoting rihizobacteria. It can increase the yield of grape by altering the physical and chemical properties and the microbial community composition of the soil.

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.

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.