Aqua­[1-(4-carb­oxy­phen­yl)-1H-imidazole-κN 3](pyridine-2,6-dicarboxyl­ato-κ3 O 2,N,O 6)copper(II) monohydrate

In the title complex, [Cu(C7H3NO4)(C10H8N2O2)(H2O)]·H2O, the CuII ion is in a slightly distorted square-pyramidal geometry. Two carboxyl­ate O atoms and one pyridine N atom from a pyridine-2,6-dicarboxyl­ate ligand chelate the CuII ion, forming two stable five-membered metalla rings. One imidazole N atom from a 1-(4-carb­oxy­phen­yl)imidazole ligand and one water mol­ecule complete the five-coordination. O—H⋯O hydrogen bonds involving the coordinated water mol­ecules and carboxyl­ate groups link the complex mol­ecules into chain-containing dinuclear macrocycles. O—H⋯O hydrogen bonds involving the uncoordinated water mol­ecules link the chains into a layer extending parallel to (10)

Sequential autologous CAR-T and allogeneic CAR-T therapy successfully treats central nervous system involvement relapsed/refractory ALL: a case report and literature review

BackgroundThe central nervous system (CNS) is the most common site of extramedullary invasion in acute lymphoblastic leukemia (ALL), and involvement of the CNS is often associated with relapse, refractory disease, and poor prognosis. Chimeric antigen receptor-T (CAR-T) cell therapy, a promising modality in cancer immunotherapy, has demonstrated significant advantages in the treatment of hematological malignancies. However, due to associated adverse reactions such as nervous system toxicity, the safety and efficacy of CAR-T cell therapy in treating CNSL remains controversial, with limited reports available.Case reportHere, we present the case of a patient with confirmed B-ALL who experienced relapse in both bone marrow (BM) and cerebrospinal fluid (CSF) despite multiple cycles of chemotherapy and intrathecal injections. The infusion of autologous CD19 CAR-T cells resulted in complete remission (CR) in both BM and CSF for 40 days. However, the patient later experienced a relapse in the bone marrow. Subsequently, allogeneic CD19 CAR-T cells derived from her brother were infused, leading to another achievement of CR in BM. Significantly, only grade 1 cytokine release syndrome (CRS) and immune effector cell-associated neurotoxicity syndrome (ICANS) events were detected during the treatment period and showed improvement with symptomatic management. During subsequent follow-up, the patient achieved a disease-free survival of 5 months and was successfully bridged to hematopoietic stem cell transplantation.ConclusionOur study provides support for the argument that CNS involvement should not be deemed an absolute contraindication to CAR-T cell therapy. With the implementation of suitable management and treatment strategies, CAR-T therapy can proficiently target tumor cells within the CNS. This treatment option may be particularly beneficial for relapsed or refractory patients, as well as those with central nervous system involvement who have shown limited response to conventional therapies. Additionally, CAR-T cell therapy may serve as a valuable bridge to allogeneic hematopoietic stem cell transplantation (allo-HSCT) in these patients

A Case of Penile Squamous Cell Carcinoma Associated with HPV58 Infection

We report the case of a 55-year-old man with penile squamous cell car- cinoma (SCC). We found a mass in the patient’s penis, which gradually increased in size. We performed a partial penectomy to remove the mass. Histopathology revealed a highly differentiated squamous cell carcinoma. Human papillomavirus (HPV) DNA was detected by polymerase chain reaction. HPV was found to be pres- ent in the squamous cell carcinoma, and sequencing analysis showed that it was type 58

Changes in habitat suitability for waterbirds of the Momoge Nature Reserve of China during 1990–2014

There is increasing empirical evidence that changes in habitat quality play an important role in determining species distributions and biodiversity. However, most research has focused on habitat quality, and we still lack approaches for tracking habitat quality dynamics. In this paper, by establishing qualitative and quantitative relationships between waterbird populations and key habitat indicators such as water abundance, food, shelter conditions and disturbance, we developed an object-oriented classification method, in conjunction with a geographic information systems (GIS) based centroid moving method, to assess habitat suitability dynamics for waterbirds at the Momoge Nature Reserve, China. Our results showed that habitat suitability improved during 1990–2000 and declined during 2000– 2014. Habitats with very good and good grades increased by 71.47 km2 (4.88%) during 1990–2000 and decreased by 200.66 km2 (13.78%) during 2000–2014. The habitat area with a good grade moved to the north, while the habitat area with a poor grade moved to the south during 1990–2014. This was mainly because the surrounding cropland area increased and shifted as oil and gas projects developed. These findings suggest that our object-oriented classification and centroid moving methods have great potential for use in biodiversity conservation and ecosystem management

Multicentre, prospective registry study of amyotrophic lateral sclerosis in mainland China (CHALSR): study protocol

Introduction Amyotrophic lateral sclerosis (ALS) is a representative rare disease characterised by progressive, fatal motor neuron degeneration. Due to the unknown aetiology and variability of the phenotypes, there are no accurate reports concerning the epidemiology or clinical characteristics of the disease. The low prevalence, as previously reported, makes it difficult to carry out studies with large samples. The aim of this study was to explore the natural history and clinical features of ALS in mainland China through a multicentre, prospective cohort study. The findings will both offer a better understanding of ALS and also support the development of a model to study other rare diseases.Methods and analysis Patients from 88 representative hospitals in different parts of mainland China will be recruited through a specially designed online data system (http://www.chalsr.net/). We aim to recruit 4752 ALS patients over a 3-year period. Baseline data will be recorded, and follow-up data will be collected every 3 months. The primary outcome is effective survival. Overall survival and indices of disease progression will be measured as the secondary outcomes.Ethics and dissemination Ethical approval has been obtained from the ethics committee of Peking University Third Hospital (M2019388). Informed written consent will be obtained from each participant. Dissemination of the study protocol and data will take place primarily through a specially designed online data system (http://www.chalsr.net/). The collective results of the study will be published in peer-reviewed journals and shared in scientific presentations.Trial registration number NCT0432867

L-Unet: A Landslide Extraction Model Using Multi-Scale Feature Fusion and Attention Mechanism

At present, it is challenging to extract landslides from high-resolution remote-sensing images using deep learning. Because landslides are very complex, the accuracy of traditional extraction methods is low. To improve the efficiency and accuracy of landslide extraction, a new model is proposed based on the U-Net model to automatically extract landslides from remote-sensing images: L-Unet. The main innovations are as follows: (1) A multi-scale feature-fusion (MFF) module is added at the end of the U-Net encoding network to improve the model’s ability to extract multi-scale landslide information. (2) A residual attention network is added to the U-Net model to deepen the network and improve the model’s ability to represent landslide features. (3) The bilinear interpolation algorithm in the decoding network of the U-Net model is replaced by data-dependent upsampling (DUpsampling) to improve the quality of the feature maps. Experimental results showed that the precision, recall, MIoU and F1 values of the L-Unet model are 4.15%, 2.65%, 4.82% and 3.37% higher than that of the baseline U-Net model, respectively. It was proven that the new model can extract landslides accurately and effectively

L-Unet: A Landslide Extraction Model Using Multi-Scale Feature Fusion and Attention Mechanism

At present, it is challenging to extract landslides from high-resolution remote-sensing images using deep learning. Because landslides are very complex, the accuracy of traditional extraction methods is low. To improve the efficiency and accuracy of landslide extraction, a new model is proposed based on the U-Net model to automatically extract landslides from remote-sensing images: L-Unet. The main innovations are as follows: (1) A multi-scale feature-fusion (MFF) module is added at the end of the U-Net encoding network to improve the model’s ability to extract multi-scale landslide information. (2) A residual attention network is added to the U-Net model to deepen the network and improve the model’s ability to represent landslide features. (3) The bilinear interpolation algorithm in the decoding network of the U-Net model is replaced by data-dependent upsampling (DUpsampling) to improve the quality of the feature maps. Experimental results showed that the precision, recall, MIoU and F1 values of the L-Unet model are 4.15%, 2.65%, 4.82% and 3.37% higher than that of the baseline U-Net model, respectively. It was proven that the new model can extract landslides accurately and effectively