Changes in paleo-groundwater levels revealed by water wells and their relationship with climate variations in imperial Southern China.

Based on records of the bottom elevations of 511 ancient water wells from published archaeological reports, we reconstructed the paleo-groundwater levels (PGWL) in urban areas of Chengdu, Changsha, Nanjing, Suzhou, Suqian, Yancheng, Fuzhou, and Guangzhou cities in southern China. Our PGWL reconstruction shows that PGWL varied in two patterns. In the inland monsoon region (Chengdu and Changsha), there was a low PGWL in Jin (AD 266-420) and South Song (AD 1127-1279), and a high PGWL in Tang (AD 618-907) and Ming (AD 1368-1644). In the coastal region (Yancheng, Fuzhou, and Guangzhou), there was a low PGWL in Jin (AD 266-420) and Ming (AD 1368-1644) but a high PGWL in Tang (AD 618-907) and Song (AD 960-1279). Via cross-wavelet transform and wavelet transform coherence analyses, we found that monsoon and temperature significantly drove the PGWL fluctuations at the inter-centennial scale. East Asian Summer Monsoon-induced precipitation has continuously affected cities in the inland monsoon area represented by Chengdu and Changsha over the past 2,500 years. It has also intermittently affected Nanjing and Suzhou when EASM intensified. In parallel, temperature influenced the PGWL in coastal cities such as Yancheng, Fuzhou, and Guangzhou via the changes in the sea level. Also, the temperature affected the PGWL in relatively inland cities during climatic anomalies such as the Medieval Warm Period and Little Ice Age. This study demonstrates the value of archaeological records in learning how climatic factors influence the PGWL variation and its mechanism.

Sparse deconvolution for background noise suppression with total variation regularization in light field microscopy.

In this Letter, we present a method aiming at background noise removal in the 3D reconstruction of light field microscopy (LFM). Sparsity and Hessian regularization are taken as two prior knowledges to process the original light field image before 3D deconvolution. Due to the noise suppression function of total variation (TV) regularization, we add the TV regularization term to the 3D Richardson-Lucy (RL) deconvolution. By comparing the light field reconstruction results of our method with another state-of-the-art method that is also based on RL deconvolution, the proposed method shows improved performance in terms of removing background noise and detail enhancement. This method will be beneficial to the application of LFM in biological high-quality imaging.

RCMNet: A deep learning model assists CAR-T therapy for leukemia.

Acute leukemia is a type of blood cancer with a high mortality rate. Current therapeutic methods include bone marrow transplantation, supportive therapy, and chemotherapy. Although a satisfactory remission of the disease can be achieved, the risk of recurrence is still high. Therefore, novel treatments are demanding. Chimeric antigen receptor-T (CAR-T) therapy has emerged as a promising approach to treating and curing acute leukemia. To harness the therapeutic potential of CAR-T cell therapy for blood diseases, reliable cell morphological identification is crucial. Nevertheless, the identification of CAR-T cells is a big challenge posed by their phenotypic similarity with other blood cells. To address this substantial clinical challenge, herein we first construct a CAR-T dataset with 500 original microscopy images after staining. Following that, we create a novel integrated model called RCMNet (ResNet18 with Convolutional Block Attention Module and Multi-Head Self-Attention) that combines the convolutional neural network (CNN) and Transformer. The model shows 99.63% top-1 accuracy on the public dataset. Compared with previous reports, our model obtains satisfactory results for image classification. Although testing on the CAR-T cell dataset, a decent performance is observed, which is attributed to the limited size of the dataset. Transfer learning is adapted for RCMNet and a maximum of 83.36% accuracy is achieved, which is higher than that of other state-of-the-art models. This study evaluates the effectiveness of RCMNet on a big public dataset and translates it to a clinical dataset for diagnostic applications.

Ginseng Rb fraction protects glia, neurons and cognitive function in a rat model of neurodegeneration.

The loss and injury of neurons play an important role in the onset of various neurodegenerative diseases, while both microgliosis and astrocyte loss or dysfunction are significant causes of neuronal degeneration. Previous studies have suggested that an extract enriched panaxadiol saponins from ginseng has more neuroprotective potential than the total saponins of ginseng. The present study investigated whether a fraction of highly purified panaxadiol saponins (termed as Rb fraction) was protective for both glia and neurons, especially GABAergic interneurons, against kainic acid (KA)-induced excitotoxicity in rats. Rats received Rb fraction at 30 mg/kg (i.p.), 40 mg/kg (i.p. or saline followed 40 min later by an intracerebroventricular injection of KA. Acute hippocampal injury was determined at 48 h after KA, and impairment of hippocampus-dependent learning and memory as well as delayed neuronal injury was determined 16 to 21 days later. KA injection produced significant acute hippocampal injuries, including GAD67-positive GABAergic interneuron loss in CA1, paralbumin (PV)-positive GABAergic interneuron loss, pyramidal neuron degeneration and astrocyte damage accompanied with reactive microglia in both CA1 and CA3 regions of the hippocampus. There was also a delayed loss of GAD67-positive interneurons in CA1, CA3, hilus and dentate gyrus. Microgliosis also became more severe 21 days later. Accordingly, KA injection resulted in hippocampus-dependent spatial memory impairment. Interestingly, the pretreatment with Rb fraction at 30 or 40 mg/kg significantly protected the pyramidal neurons and GABAergic interneurons against KA-induced acute excitotoxicity and delayed injury. Rb fraction also prevented memory impairments and protected astrocytes from KA-induced acute excitotoxicity. Additionally, microglial activation, especially the delayed microgliosis, was inhibited by Rb fraction. Overall, this study demonstrated that Rb fraction protected both astrocytes and neurons, especially GABAergic interneurons, and maintained microglial homeostasis against KA-induced excitotoxicity. Therefore, Rb fraction has the potential to prevent and treat neurodegenerative diseases.