小婴儿腰椎穿刺脑脊液参考值

研究背景既往有关脑脊液(CSF)参考值的研究为单中心研究,且样本量较小,因此其应用价值有限。研究新知这项多中心横断面调查研究确定了不同日龄段婴儿的CSF参考值,并且提供了日龄相关CSF百分位参考曲线。

An orbitofrontal cortex to midbrain projection modulates neuropathic pain

Neuropathic pain is a long term and common pain disorder in clinics that is refractory to treatment,however,the neural substrates and underlying mechanisms are poorly understood.Using the com bination of neuronal mapping,optogenetics,chemogenetics,eletrophysiological recording,in vivo fiber photometry and behavioral testing,we previously identified a new neural circuit of BLA-mPFC-vIPAG and its key role in encoding and modulation of the spared nerve injury(SNI)-induced neuropathic pain..Here we report that the V M-vlOFC-vIPAG circuit modulates neuropathic pain and dissects the underlying mechanisms at cellular and circuitry level.

Epitranscriptomic Regulation of NMDA Receptors Rears its Ugly Head in Chemotherapy-Induced Neuropathic Pain

A number of different cancer chemotherapy agents such as cisplatin,oxaliplatin,and paclitaxel can lead to nerve damage,thereby giving rise to neuropathic pain states that present with mechanical and cold allodynia[1].Although these pain conditions often resolve after completion of the chemotherapy,a significant portion of patients exhibit longlasting pain that can persist longer than 12 months with a negative impact on the quality of life of affected individuals[1].

Lesion-symptom mapping with NIHSS sub-scores in ischemic stroke patients

Background Lesion-symptom mapping(LSM)is a statistical technique to investigate the population-specific relationship between structural integrity and post-stroke clinical outcome.In clinical practice,patients are commonly evaluated using the National Institutes of Health Stroke Scale(NIHSS),an 11-domain clinical score to quantitate neurological deficits due to stroke.So far,LSM studies have mostly used the total NIHSS score for analysis,which might not uncover subtle structure–function relationships associated with the specific sub-domains of the NIHSS evaluation.Thus,the aim of this work was to investigate the feasibility to perform LSM analyses with sub-score information to reveal category-specific structure–function relationships that a total score may not reveal.Methods Employing a multivariate technique,LSM analyses were conducted using a sample of 180 patients with NIHSS assessment at 48-hour post-stroke from the ESCAPE trial.The NIHSS domains were grouped into six categories using two schemes.LSM was conducted for each category of the two groupings and the total NIHSS score.Results Sub-score LSMs not only identify most of the brain regions that are identified as critical by the total NIHSS score but also reveal additional brain regions critical to each function category of the NIHSS assessment without requiring extensive,specialised assessments.Conclusion These findings show that widely available sub-scores of clinical outcome assessments can be used to investigate more specific structure–function relationships,which may improve predictive modelling of stroke outcomes in the context of modern clinical stroke assessments and neuroimaging.

eTumorType, An Algorithm of DiscriminatingCancer Types for Circulating Tumor Cells orCell-free DNAs in Blood

With the technology development on detecting circulating tumor cells(CTCs) and cellfree DNAs(cf DNAs) in blood, serum, and plasma, non-invasive diagnosis of cancer becomes promising. A few studies reported good correlations between signals from tumor tissues and CTCs or cf DNAs, making it possible to detect cancers using CTCs and cf DNAs. However, the detection cannot tell which cancer types the person has. To meet these challenges, we developed an algorithm,e Tumor Type, to identify cancer types based on copy number variations(CNVs) of the cancer founding clone. e Tumor Type integrates cancer hallmark concepts and a few computational techniques such as stochastic gradient boosting, voting, centroid, and leading patterns. e Tumor Type has been trained and validated on a large dataset including 18 common cancer types and 5327 tumor samples. e Tumor Type produced high accuracies(0.86–0.96) and high recall rates(0.79–0.92) for predicting colon, brain, prostate, and kidney cancers. In addition, relatively high accuracies(0.78–0.92)and recall rates(0.58–0.95) have also been achieved for predicting ovarian, breast luminal, lung, endometrial, stomach, head and neck, leukemia, and skin cancers. These results suggest that e Tumor Type could be used for non-invasive diagnosis to determine cancer types based on CNVs of CTCs and cf DNAs.

Network Analysis Reveals A Signaling RegulatoryLoop in PIK3CA-mutated Breast Cancer Predicting Survival Outcome

Mutated genes are rarely common even in the same pathological type between cancer patients and as such, it has been very challenging to interpret genome sequencing data and difficult to predict clinical outcomes. PIK3 CA is one of a few genes whose mutations are relatively popular in tumors. For example, more than 46.6% of luminal-A breast cancer samples have PIK3 CA mutated, whereas only 35.5% of all breast cancer samples contain PIK3 CA mutations. To understand the function of PIK3 CA mutations in luminal A breast cancer, we applied our recentlyproposed Cancer Hallmark Network Framework to investigate the network motifs in the PIK3CA-mutated luminal A tumors. We found that more than 70% of the PIK3CA-mutated luminal A tumors contain a positive regulatory loop where a master regulator(PDGF-D), a second regulator(FLT1) and an output node(SHC1) work together. Importantly, we found the luminal A breast cancer patients harboring the PIK3 CA mutation and this positive regulatory loop in their tumors have significantly longer survival than those harboring PIK3 CA mutation only in their tumors. These findings suggest that the underlying molecular mechanism of PIK3 CA mutations in luminal A patients can participate in a positive regulatory loop, and furthermore the positive regulatory loop(PDGF-D/FLT1/SHC1) has a predictive power for the survival of the PIK3 CAmutated luminal A patients.

Biallelic mutations in UGDH cause congenital microcephaly

Hengel et al recently reported that bi-allelic loss-of-function mutations in UDP-Glucose 6-Dehydrogenase(UGDH)caused a severe epileptic encephalopathy syndrome-Jamuar syndrome(OMIM#618792).1 The functional studies partially recapitulated the clinical phenotypes in the patient-derived cerebral organoid.A reduced number of proliferating neuronal progenitors in cerebral organoids was shown,which is a critical mechanism in congenital microcephaly(CM)whose patients were born with an occipitofrontal circumference(OCF)more than 2 standard deviations below average for age and sex.However,none of the reported patients in the article presented the phenotype as CM.