The Role of NMDA Receptors in Alzheimer’s Disease

In Alzheimer’s disease (AD), early synaptic dysfunction is associated with the increased oligomeric amyloid-beta peptide, which causes NMDAR-dependent synaptic depression and spine elimination. Memantine, low-affinity NMDAR channel blocker, has been used in the treatment of moderate to severe AD. However, clear evidence is still deficient in demonstrating the underlying mechanisms and a relationship between NMDARs dysfunction and AD. This review focuses on not only changes in expression of different NMDAR subunits, but also some unconventional modes of NMDAR action

Effect of laser irradiation on cell function and its implications in Raman spectroscopy

Lasers are instrumental in advanced bioimaging and Raman spectroscopy. However, they are also well known for their destructive effects on living organisms, leading to concerns about the adverse effects of laser technologies. To implement Raman spectroscopy for cell analysis and manipulation, such as Raman activated cell sorting, it is crucial to identify non-destructive conditions for living cells. Here, we evaluated quantitatively the effect of 532 nm laser irradiation on bacterial cell fate and growth at the single-cell level. Using a purpose-built microfluidic platform, we were able to quantify the growth characteristics i.e. specific growth rate and lag time of individual cells as well as the survival rate of a population in conjunction with Raman spectroscopy. Representative Gram-negative and Gram-positive species show a similar trend in response to laser irradiation dose. Laser irradiation could compromise physiological function of cells and the degree of destruction is both dose and strain dependent, ranging from reduced cell growth to a complete loss of cell metabolic activity and finally to physical disintegration. Gram-positive bacterial cells are more susceptible than Gram-negative bacterial strains to irradiation-induced damage. By directly correlating Raman acquisition with single cell growth characteristics, we provide evidence of non-destructive characteristics of Raman spectroscopy on individual bacterial cells. However, while strong Raman signals can be obtained without causing cell death, the variety of responses from different strains and from individual cells justify careful evaluation of Raman acquisition conditions if cell viability is critical

Comparison of Intergrowth-21st and Fenton growth standards to evaluate and predict the postnatal growth in eastern Chinese preterm infants

ObjectivesThe aim of this article was to compare the differences between Intergrowth-21st (IG-21) and Fenton growth standards in the classification of intrauterine and extrauterine growth restriction (EUGR) in eastern Chinese preterm infants, and detect which one can better relate to neonatal diseases and predict the physical growth outcomes at 3–5 years old.MethodsPremature infants admitted to a tertiary pediatric hospital in Shanghai, China, from 2016 to 2018 were enrolled. Prenatal information, neonatal diseases during hospitalization, and anthropometric data (weight, height, and head circumference) at birth and at discharge were collected and analyzed. Physical growth outcomes (short stature, thinness, and overweight) were examined by telephone investigations in 2021 at age 3–5 years.ResultsThe medium gestational age and birth weight of the included 1,065 preterm newborns were 33.6 weeks and 1,900 g, respectively. The IG-21 curves diagnosed more newborns with small for gestational age (SGA) (19% vs. 14.7%) and fewer newborns with longitudinal EUGR on height (25.5% vs. 27.9%) and head circumference (17.9% vs. 24.7%) compared to Fenton curves. Concordances between Fenton and IG-21 standards were substantial or almost perfect in the classification of SGA and longitudinal EUGR, but minor in cross-sectional EUGR. EUGR identified by Fenton curves was better related to neonatal diseases than IG-21 curves. There were no statistical significances in the prediction of short stature, thinness, and overweight at 3–5 years old between the two charts.ConclusionsIG-21 growth standards are not superior to Fenton in assessing preterm growth and development in the eastern Chinese population

Artificial intelligence-aided rapid and accurate identification of clinical fungal infections by single-cell Raman spectroscopy

Integrating artificial intelligence and new diagnostic platforms into routine clinical microbiology laboratory procedures has grown increasingly intriguing, holding promises of reducing turnaround time and cost and maximizing efficiency. At least one billion people are suffering from fungal infections, leading to over 1.6 million mortality every year. Despite the increasing demand for fungal diagnosis, current approaches suffer from manual bias, long cultivation time (from days to months), and low sensitivity (only 50% produce positive fungal cultures). Delayed and inaccurate treatments consequently lead to higher hospital costs, mobility and mortality rates. Here, we developed single-cell Raman spectroscopy and artificial intelligence to achieve rapid identification of infectious fungi. The classification between fungi and bacteria infections was initially achieved with 100% sensitivity and specificity using single-cell Raman spectra (SCRS). Then, we constructed a Raman dataset from clinical fungal isolates obtained from 94 patients, consisting of 115,129 SCRS. By training a classification model with an optimized clinical feedback loop, just 5 cells per patient (acquisition time 2 s per cell) made the most accurate classification. This protocol has achieved 100% accuracies for fungal identification at the species level. This protocol was transformed to assessing clinical samples of urinary tract infection, obtaining the correct diagnosis from raw sample-to-result within 1 h

SPINN: Synergistic Progressive Inference of Neural Networks over Device and Cloud

Despite the soaring use of convolutional neural networks (CNNs) in mobile applications, uniformly sustaining high-performance inference on mobile has been elusive due to the excessive computational demands of modern CNNs and the increasing diversity of deployed devices. A popular alternative comprises offloading CNN processing to powerful cloud-based servers. Nevertheless, by relying on the cloud to produce outputs, emerging mission-critical and high-mobility applications, such as drone obstacle avoidance or interactive applications, can suffer from the dynamic connectivity conditions and the uncertain availability of the cloud. In this paper, we propose SPINN, a distributed inference system that employs synergistic device-cloud computation together with a progressive inference method to deliver fast and robust CNN inference across diverse settings. The proposed system introduces a novel scheduler that co-optimises the early-exit policy and the CNN splitting at run time, in order to adapt to dynamic conditions and meet user-defined service-level requirements. Quantitative evaluation illustrates that SPINN outperforms its state-of-the-art collaborative inference counterparts by up to 2x in achieved throughput under varying network conditions, reduces the server cost by up to 6.8x and improves accuracy by 20.7% under latency constraints, while providing robust operation under uncertain connectivity conditions and significant energy savings compared to cloud-centric execution.Comment: Accepted at the 26th Annual International Conference on Mobile Computing and Networking (MobiCom), 202

Ultrasound-mediated DNA transfer for bacteria

In environmental microbiology, the most commonly used methods of bacterial DNA transfer are conjugation and electroporation. However, conjugation requires physical contact and cell–pilus–cell interactions; electroporation requires low-ionic strength medium and high voltage. These limitations have hampered broad applications of bacterial DNA delivery. We have employed a standard low frequency 40 kHz ultrasound bath to successfully transfer plasmid pBBR1MCS2 into Pseudomonas putida UWC1, Escherichia coli DH5 and Pseudomonas fluorescens SBW25 with high efficiency. Under optimal conditions: ultrasound exposure time of 10 s, 50 mM CaCl2, temperature of 22°C, plasmid concentration of 0.8 ng/µl, P. putida UWC1 cell concentration of 2.5 x 109 CFU (colony forming unit)/ml and reaction volume of 500 µl, the efficiency of ultrasound DNA delivery (UDD) was 9.8 ± 2.3 x 10–6 transformants per cell, which was nine times more efficient than conjugation, and even four times greater than electroporation. We have also transferred pBBR1MCS2 into E. coli DH5 and P. fluorescens SBW25 with efficiencies of 1.16 ± 0.13 x 10–6 and 4.33 ± 0.78 x 10–6 transformants per cell, respectively. Low frequency UDD can be readily scaled up, allowing for the application of UDD not only in laboratory conditions but also on an industrial scale