Argon laser treatment of central serous chorioretinopathy

AIM: To observe the efficacy of the argon laser photocoagulation treatment of central serous chorioretinopathy(CSC). METHODS: The treatment groups: 18 patients(18 eyes), argon laser photocoagulation and oral jolethin, vitamin B1, inosine and venoruton tablets. Control group: 18 patients(18 eyes), oral lecithin complex iodine, vitamin B1, inosine, venoruton tablets. Foveal thickness and neuroepithelial layer detachment range were measured by optical coherence tomography(OCT)before treatment, after 1 month and 3 months post-operation to compare the decline in value of foveal thickness and neuroepithelial layer detachment range of the two groups. RESULTS: After 1 month of treatment, the decline in value of the center foveal thickness: the value of treatment group was 256±72μm; the value of the control group was 82±57μm, and the difference of the two groups, P <0.05; the decline in value of neuroepithelial layer detachment range: the value of the treatment group was 3 548±168μm, the value of the control group was 1 520±143μm, And the difference of the two groups, P<0.05. After three months of treatment, the decline in value of the center foveal thickness: the value of treatment group was 383±75μm, the value of the control group was 312±67 μm, and the difference of the two groups, P<0.05; decline in value of neuroepithelial layer detachment range: the value of the treatment group was 4 908±172μm, the value of the control group was 4 211±153μm, and the difference of the two groups, P <0.05. The differences were statistically significant between the treatment and the control groups(two independent samples t-test). CONCLUSION:Argon laser photocoagulation treatment of CSC is an effective treatment method and can significantly shorten the course

Local-to-Global Information Communication for Real-Time Semantic Segmentation Network Search

Neural Architecture Search (NAS) has shown great potentials in automatically designing neural network architectures for real-time semantic segmentation. Unlike previous works that utilize a simplified search space with cell-sharing way, we introduce a new search space where a lightweight model can be more effectively searched by replacing the cell-sharing manner with cell-independent one. Based on this, the communication of local to global information is achieved through two well-designed modules. For local information exchange, a graph convolutional network (GCN) guided module is seamlessly integrated as a communication deliver between cells. For global information aggregation, we propose a novel dense-connected fusion module (cell) which aggregates long-range multi-level features in the network automatically. In addition, a latency-oriented constraint is endowed into the search process to balance the accuracy and latency. We name the proposed framework as Local-to-Global Information Communication Network Search (LGCNet). Extensive experiments on Cityscapes and CamVid datasets demonstrate that LGCNet achieves the new state-of-the-art trade-off between accuracy and speed. In particular, on Cityscapes dataset, LGCNet achieves the new best performance of 74.0\% mIoU with the speed of 115.2 FPS on Titan Xp.Comment: arXiv admin note: text overlap with arXiv:1909.0679

5-(4-Chloro­phen­yl)-1H-tetra­zole

The two independent mol­ecules of the title compound, C7H5ClN4, both lie on a twofold rotation axis that passes through the centroids of the five- and six-membered rings and the attached Cl C atom. One molecule is nearly planar [dihedral angle between rings = 0.22 (6)°], whereas the other is significantly twisted [dihedral angle = 17.38 (6)°]. In the crystal, adjacent mol­ecules are linked by N—H⋯N hydrogen bonds into a chain structure

{2-[2-(Carb­oxy­meth­oxy)­phen­oxy]acetato}[2,2′-(o-phenyl­enedi­oxy)diacetic acid]sodium 4,4′-bipyridine hemisolvate monohydrate

In the title compound, [Na(C10H9O6)(C10H10O6)]·0.5C10H8N2·H2O, the Na atom is eight-coordinated in an distorted dicapped-octa­hedral geometry by eight O atoms from a 2-(2-carb­oxy­meth­oxy­phen­oxy)acetate (o-BDOAH) anion and a 2,2′-(o-phenyl­enedi­oxy)diacetic acid (o-BDOAH2) mol­ecule. The uncoordinated 4,4′-bipyridine mol­ecule is arranged around an inversion center and exhibits rotational disorder. A three-dimensional supra­molecular network is built up in the crystal through O—H⋯O and O—H⋯N hydrogen bonds between the uncoordinated water mol­ecule, the uncoordinated 4,4′-bipyridine mol­ecule and the sodium complex mol­ecule

Electrocatalysis of Oxygen Reduction on Te-Modified Platinum Stepped Crystal Surfaces

Te-modified platinum single-crystal surfaces in the [011̅] zone have been used as model electrocatalysts for oxygen reduction reaction (ORR). The results clearly show that (1) except for Pt(111), all other electrodes display enhanced ORR activity when Te is deposited on the surface; (2) the intrinsic ORR activity for Pt(hkl) decreases in the order of Pt(322) > Pt(755) > Pt(977) > Pt(111) > Pt(311) > Pt(100), while the enhancement factor for ORR with Te modification decreases in the order of Pt(100) > Pt(311) > Pt(977) > Pt(755) > Pt(322); (3) metallic Te and its charge transfer to Pt as well as the consequent lower d-band center and OHad binding energy are probably the reasons for the enhanced electrocatalysis for ORR with Te modification; and (4) the inhibition of Te at Pt(111) as well as the smaller extent for the enhancement of Te at Pt(S)-[n(111) × (100)] with longer terraces in the kinetic region for ORR are a result of partial oxidation of Te. The weaker electronic interaction of Te with the Pt substrate is probably the origin of its facile oxidation at lower potential. Our results imply that modification of Pt with species that can transfer electrons to Pt may be an efficient strategy to enhance the ORR activity.This work was supported by the National Natural Science Foundation of China (No. 22172151, 21972131, and 21832004). E.H. gratefully acknowledged the International Professorship by USTC and financial support from the Ministerio de Ciencia e Innovación (project PID2022–137350NB-I00)

Knowledge-tuning Large Language Models with Structured Medical Knowledge Bases for Reliable Response Generation in Chinese

Large Language Models (LLMs) have demonstrated remarkable success in diverse natural language processing (NLP) tasks in general domains. However, LLMs sometimes generate responses with the hallucination about medical facts due to limited domain knowledge. Such shortcomings pose potential risks in the utilization of LLMs within medical contexts. To address this challenge, we propose knowledge-tuning, which leverages structured medical knowledge bases for the LLMs to grasp domain knowledge efficiently and facilitate reliable response generation. We also release cMedKnowQA, a Chinese medical knowledge question-answering dataset constructed from medical knowledge bases to assess the medical knowledge proficiency of LLMs. Experimental results show that the LLMs which are knowledge-tuned with cMedKnowQA, can exhibit higher levels of accuracy in response generation compared with vanilla instruction-tuning and offer a new reliable way for the domain adaptation of LLMs.Comment: 11 pages, 5 figure

Learn by Oneself: Exploiting Weight-Sharing Potential in Knowledge Distillation Guided Ensemble Network

Recent CNNs (convolutional neural networks) have become more and more compact. The elegant structure design highly improves the performance of CNNs. With the development of knowledge distillation technique, the performance of CNNs gets further improved. However, existing knowledge distillation guided methods either rely on offline pretrained high-quality large teacher models or online heavy training burden. To solve the above problems, we propose a feature-sharing and weight-sharing based ensemble network (training framework) guided by knowledge distillation (EKD-FWSNet) to make baseline models stronger in terms of representation ability with less training computation and memory cost involved. Specifically, motivated by getting rid of the dependence of offline pretrained teacher model, we design an end-to-end online training scheme to optimize EKD-FWSNet. Motivated by decreasing the online training burden, we only introduce one auxiliary classmate branch to construct multiple forward branches, which will then be integrated as ensemble teacher to guide baseline model. Compared to previous online ensemble training frameworks, EKD-FWSNet can provide diverse output predictions without relying on increasing auxiliary classmate branches. Motivated by maximizing the optimization power of EKD-FWSNet, we exploit the representation potential of weight-sharing blocks and design efficient knowledge distillation mechanism in EKD-FWSNet. Extensive comparison experiments and visualization analysis on benchmark datasets (CIFAR-10/100, tiny-ImageNet, CUB-200 and ImageNet) show that self-learned EKD-FWSNet can boost the performance of baseline models by large margin, which has obvious superiority compared to previous related methods. Extensive analysis also proves the interpretability of EKD-FWSNet. Our code is available at https://github.com/cv516Buaa/EKD-FWSNet

Generation of Human Epidermis-Derived Mesenchymal Stem Cell-like Pluripotent Cells and their reprogramming in mouse chimeras

Stem cells can be derived from the embryo (embryonic stem cells, ESCs), from adult tissues (adult stem cells, ASCs), and by induction of fibroblasts (induced pluripotent stem cells, iPSs). Ethical problems, immunological rejection, and difficulties in obtaining human tissues limit the use of ESCs in clinical medicine. Induced pluripotent stem cells are difficult to maintain in vitro and carry a greater risk of tumor formation. Furthermore, the complexity of maintenance and propagation is especially difficult in the clinic. Adult stem cells can be isolated from several adult tissues and present the possibility of self-transplantation for the clinical treatment of a variety of human diseases. Recently, several ASCs have been successfully isolated and cultured in vitro, including hematopoietic stem cells (HSCs) , mesenchymal stem cells (MSCs), epidermis stem cells, neural stem cells (NSCs), adipose-derived stem cells (ADSCs), islet stem cells, and germ line stem cells. Human mesenchymal stem cells originate mainly from bone marrow, cord blood, and placenta, but epidermis-derived MSCs have not yet been isolated. We isolated small spindle-shaped cells with strong proliferative potential during the culture of human epidermis cells and designed a medium to isolate and propagate these cells. They resembled MSCs morphologically and demonstrated pluripotency in vivo; thus, we defined these cells as human epidermis-derived mesenchymal stem cell-like pluripotent cells (hEMSCPCs). These hEMSCPCs present a possible new cell resource for tissue engineering and regenerative medicine