Terrestrial carbon storage and sequestration potential of institutionally managed estates

Ph. D. ThesisMany institutions have declared a climate emergency and are committed to ambitious net-zero carbon aims. However, few institutional carbon management plans consider the terrestrial carbon store of the estate in a quantitative or qualitative way. Using Newcastle University as a case study, this research demonstrated ways to quantify and potentially augment the soil and tree carbon stocks of institutional estates by changes in land management. The terrestrial carbon store of Newcastle University’s estate was quantified with field work, and scenarios of the off-setting of institutional carbon emissions were derived by considering alternative land management. Additionally, the application of wheat straw biomass and its biochar to urban soil was investigated for carbon sequestration. To quantify the current carbon storage baseline of the institutional estate, soil and tree carbon was surveyed for two research farms, campus green spaces, and a sports field. The total terrestrial carbon stock of Newcastle University’s estate was found to be 17 times greater than the annual institutional CO2 equivalents-C emissions in 2019-20. Newcastle University could off-set half of its institutional CO2 equivalents-C emissions over a period of 40 years by converting its farms into woodland. Reverting farm management to practices shown on old maps from 1900 with more permanent grasslands could off-set 64 percent of institutional CO2 equivalents-C emissions over a period of 5 years. Other measure such as doubling the number of free-standing trees on the farms, converting all lawns on the central campus into urban woodland, or amending the Newcastle Helix brownfield reclamation site soil with 2% biochar would off-set less than 3 percent of institutional emissions over 40 years. Interviews with estate, farm and carbon managers revealed reluctance to accept the dramatic land management changes which would be needed for tangible off-setting of institutional emissions, but it will be difficult to achieve net-zero carbon emission aims without serious consideration of off-setting opportunities in Newcastle University’s estate.UKCRI

Weighted gene co-expression network analysis and CIBERSORT screening of key genes related to m6A methylation in Hirschsprung’s disease

Hirschsprung’s disease (HSCR) is a neural crest disease that results from the failure of enteric neural crest cells (ENCCs) to migrate to the corresponding intestinal segment. The RET gene, which regulates enteric neural crest cell proliferation and migration, is considered one of the main risk factors for HSCR and is commonly used to construct HSCR mouse models. The epigenetic mechanism of m6A modification is involved in HSCR. In this study, we analyzed the GEO database (GSE103070) for differentially expressed genes (DEGs) and focused on m6A–related genes. Comparing the RNA-seq data of Wide Type and RET Null, a total of 326 DEGs were identified, of which 245 genes were associated with m6A. According to the CIBERSORT analysis, the proportion of Memory B-cell in RET Null was significantly higher than that of Wide Type. Venn diagram analysis was used to identify key genes in the selected memory B-cell modules and DEGs associated with m6A. Enrichment analysis showed that seven genes were mainly involved in focal adhesion, HIV infection, actin cytoskeleton organization and regulation of binding. These findings could provide a theoretical basis for molecular mechanism studies of HSCR

Targeted aspect based multimodal sentiment analysis:an attention capsule extraction and multi-head fusion network

Multimodal sentiment analysis has currently identified its significance in a variety of domains. For the purpose of sentiment analysis, different aspects of distinguishing modalities, which correspond to one target, are processed and analyzed. In this work, we propose the targeted aspect-based multimodal sentiment analysis (TABMSA) for the first time. Furthermore, an attention capsule extraction and multi-head fusion network (EF-Net) on the task of TABMSA is devised. The multi-head attention (MHA) based network and the ResNet-152 are employed to deal with texts and images, respectively. The integration of MHA and capsule network aims to capture the interaction among the multimodal inputs. In addition to the targeted aspect, the information from the context and the image is also incorporated for sentiment delivered. We evaluate the proposed model on two manually annotated datasets. the experimental results demonstrate the effectiveness of our proposed model for this new task

Clinical Efficacy and Safety of Acupuncture Rehabilitation for Post-stroke Depression: A Systematic Review and Meta-analysis

Objective: The most important and common psychiatric disorders after stroke include post-stroke depression, which can lead to a variety of negative health outcomes. This study was calculated to estimate the security and effectiveness of acupuncture rehabilitation in curative effects for post-stroke depression patients. Methods: As of July 2022, PubMed, Embase, Web of Science, Cochrane Library, and China National Knowledge Infrastructure were searched through electronic databases. Eligibility criteria RCTs evaluate RCTs of acupuncture rehabilitation on treatment events in depressed patients after stroke, compared to a control group. Results: Eight studies were included (n = 16,422). When combined with antidepressant/sham acupuncture efficacy, acupuncture intervention observably reduced HAMD scores (MD= -0.55,95% CI= -1.57 to -0.48, P=0.30, I²= 0%). Meanwhile, acupuncture rehabilitation also reduced BI scores (MD= 1.87,95%CI= -3.77-7.51, P=0.51, I²= 0%) and CGI-S score (MD=0.43,95% CI = 0.06-0.77, P =0.01, I² = 0%) compared with antidepressants / sham acupuncture. Second, the occurrence rate of combined negative events was dramatically lesser in the acupuncture groups, as indicated by the SERS scores (MD= -4.85,95% CI= 5.67 to -4.04, P <0.00001, I² = 0%) of the acupuncture groups and the antidepressant/sham acupuncture groups. Furthermore, the overall clinical outcome was observably better in the acupuncture groups (MD=1.58,95% CI =0.813.09, P =0.18, I² = 0%). Conclusion: Acupuncture rehabilitation intervention for post-stroke depression is safer and more effective than antidepressant/sham acupuncture

The global landscape of approved antibody therapies

Antibody therapies have become an important class of therapeutics in recent years as they have exhibited outstanding efficacy and safety in the treatment of several major diseases including cancers, immune-related diseases, infectious disease and hematological disease. There has been significant progress in the global research and development landscape of antibody therapies in the past decade. In this review, we have collected available data from the Umabs Antibody Therapies Database (Umabs-DB, https://umabs.com) as of 30 June 2022. The Umabs-DB shows that 162 antibody therapies have been approved by at least one regulatory agency in the world, including 122 approvals in the US, followed by 114 in Europe, 82 in Japan and 73 in China, whereas biosimilar, diagnostic and veterinary antibodies are not included in our statistics. Although the US and Europe have been at the leading position for decades, rapid advancement has been witnessed in Japan and China in the past decade. The approved antibody therapies include 115 canonical antibodies, 14 antibody-drug conjugates, 7 bispecific antibodies, 8 antibody fragments, 3 radiolabeled antibodies, 1 antibody-conjugate immunotoxin, 2 immunoconjugates and 12 Fc-Fusion proteins. They have been developed against 91 drug targets, of which PD-1 is the most popular, with 14 approved antibody-based blockades for cancer treatment in the world. This review outlined the global landscape of the approved antibody therapies with respect to the regulation agencies, therapeutic targets and indications, aiming to provide an insight into the trends of the global development of antibody therapies

Revisiting Evaluation Metrics for Semantic Segmentation: Optimization and Evaluation of Fine-grained Intersection over Union

Semantic segmentation datasets often exhibit two types of imbalance: \textit{class imbalance}, where some classes appear more frequently than others and \textit{size imbalance}, where some objects occupy more pixels than others. This causes traditional evaluation metrics to be biased towards \textit{majority classes} (e.g. overall pixel-wise accuracy) and \textit{large objects} (e.g. mean pixel-wise accuracy and per-dataset mean intersection over union). To address these shortcomings, we propose the use of fine-grained mIoUs along with corresponding worst-case metrics, thereby offering a more holistic evaluation of segmentation techniques. These fine-grained metrics offer less bias towards large objects, richer statistical information, and valuable insights into model and dataset auditing. Furthermore, we undertake an extensive benchmark study, where we train and evaluate 15 modern neural networks with the proposed metrics on 12 diverse natural and aerial segmentation datasets. Our benchmark study highlights the necessity of not basing evaluations on a single metric and confirms that fine-grained mIoUs reduce the bias towards large objects. Moreover, we identify the crucial role played by architecture designs and loss functions, which lead to best practices in optimizing fine-grained metrics. The code is available at \href{https://github.com/zifuwanggg/JDTLosses}{https://github.com/zifuwanggg/JDTLosses}.Comment: NeurIPS 202

Genome Assembly and Annotation of a High-Polymalic Acid (PMLA) Producing Strain Aureobasidium melanogenum CGMCC18996 and Analysis of Its Key Proteins Related to PMLA Synthesis

In this study, we applied PacBio Sequel II and Illumina NovaSeq 6000 sequencing platforms to sequence the genome of a high-polymalic acid (PMLA)-producing strain, Aureobasidium melanogenum CGMCC18996, and used different assemblers to obtain a high-quality genome assembly, which was then annotated using transcriptomic data. The results indicated a total of 6 202 genes were found in the A. melanogenum genome, mainly involved in carbohydrate transport and metabolism, amino acid transport and metabolism, post-translational modification, RNA processing and modification. Meanwhile, functional annotation revealed that most genes in the genome were related to peroxisome in the strain. Transmission electron microscopy (TEM) indicated the existence of a circular peroxisome-like (glyoxysome) structure in the cells, demonstrating the ability to malic acid through the glyoxylate cycle. Finally, we predicted the protein structures of two enzymes related to PMLA biosynthesis, phosphoenolpyruvate carboxykinase (PCKA) and malate synthase (MASY). It was found that the enzymes could have the ability to synthesize malic acid. This study could provide a reference for metabolism regulation in A. melanogenum for improved PMLA production, and the assembled genome has been uploaded to the database, which could provide the basis for the future development and utilization of A. melanogenum CGMCC18996

A preliminary evaluation of targeted nanopore sequencing technology for the detection of Mycobacterium tuberculosis in bronchoalveolar lavage fluid specimens

ObjectiveTo evaluate the efficacy of targeted nanopore sequencing technology for the detection of Mycobacterium tuberculosis(M.tb.) in bronchoalveolar lavage fluid(BALF) specimens.MethodsA prospective study was used to select 58 patients with suspected pulmonary tuberculosis(PTB) at Henan Chest Hospital from January to October 2022 for bronchoscopy, and BALF specimens were subjected to acid-fast bacilli(AFB) smear, Mycobacterium tuberculosis MGIT960 liquid culture, Gene Xpert MTB/RIF (Xpert MTB/RIF) and targeted nanopore sequencing (TNS) for the detection of M.tb., comparing the differences in the positive rates of the four methods for the detection of patients with different classifications.ResultsAmong 58 patients with suspected pulmonary tuberculosis, there were 48 patients with a final diagnosis of pulmonary tuberculosis. Using the clinical composite diagnosis as the reference gold standard, the sensitivity of AFB smear were 27.1% (95% CI: 15.3-41.8); for M.tb culture were 39.6% (95% CI: 25.8-54.7); for Xpert MTB/RIF were 56.2% (95% CI: 41.2-70.5); for TNS were 89.6% (95% CI: 77.3-96.5). Using BALF specimens Xpert MTB/RIF and/or M.tb. culture as the reference standard, TNS showed 100% (30/30) sensitivity. The sensitivity of NGS for pulmonary tuberculosis diagnosis was significantly higher than Xpert MTB/RIF, M.tb. culture, and AFB smear. Besides, P values of &lt;0.05 were considered statistically significant.ConclusionUsing a clinical composite reference standard as a reference gold standard, TNS has the highest sensitivity and consistency with clinical diagnosis, and can rapidly and efficiently detect PTB in BALF specimens, which can aid to improve the early diagnosis of suspected tuberculosis patients

Whole exome sequencing of insulinoma reveals recurrent T372R mutations in YY1

Functional pancreatic neuroendocrine tumours (PNETs) are mainly represented by insulinoma, which secrete insulin independent of glucose and cause hypoglycaemia. The major genetic alterations in sporadic insulinomas are still unknown. Here we identify recurrent somatic T372R mutations in YY1 by whole exome sequencing of 10 sporadic insulinomas. Further screening in 103 additional insulinomas reveals this hotspot mutation in 30% (34/113) of all tumours. T372R mutation alters the expression of YY1 target genes in insulinomas. Clinically, the T372R mutation is associated with the later onset of tumours. Genotyping of YY1, a target of mTOR inhibitors, may contribute to medical treatment of insulinomas. Our findings highlight the importance of YY1 in pancreatic β-cells and may provide therapeutic targets for PNETs