TRLS: A Time Series Representation Learning Framework via Spectrogram for Medical Signal Processing

Representation learning frameworks in unlabeled time series have been proposed for medical signal processing. Despite the numerous excellent progresses have been made in previous works, we observe the representation extracted for the time series still does not generalize well. In this paper, we present a Time series (medical signal) Representation Learning framework via Spectrogram (TRLS) to get more informative representations. We transform the input time-domain medical signals into spectrograms and design a time-frequency encoder named Time Frequency RNN (TFRNN) to capture more robust multi-scale representations from the augmented spectrograms. Our TRLS takes spectrogram as input with two types of different data augmentations and maximizes the similarity between positive ones, which effectively circumvents the problem of designing negative samples. Our evaluation of four real-world medical signal datasets focusing on medical signal classification shows that TRLS is superior to the existing frameworks.Comment: This paper is accept by ICASSP 2024. This is a more detailed versio

A New Parallel Processor Architecture for Genus 2 Hyperelliptic Curve Cryptosystems

Hyperelliptic curve cryptosystem (HECC) is much more efficient than RSA and elliptic curve cryptosystem (ECC) for its shorter key lengths. Hyperelliptic curve cryptosystems can be sped up by parallel execution on hardware accelerators, yet none of previous efforts can sufficiently support parallel processing with reasonable resources. In this paper, we propose a new parallel processor architecture for HECC, which supports sufficient instruction-level parallel processing. In the architecture, Parallel finite field (FF) cores are designed, and each core consists of a control unit, a register file, an ALU and a ROM. Instruction-level parallelism (ILP) with pipeline is achieved in this architecture. The results show that the implementation can achieve much better performance than other hardware implementations done to date.http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000312667600034&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=8e1609b174ce4e31116a60747a720701Computer Science, Hardware & ArchitectureEngineering, Electrical & ElectronicTelecommunicationsEICPCI-S(ISTP)

Three amino acids of a heptapeptide-induced antibody are responsible for recognition of SV40 structural proteins

The prevalence of tobacco use in people with schizophrenia is much higher than in general population, which indicates a close relationship between nicotine addiction and schizophrenia. However, the molecular mechanism underlying the high comorbidity of tobacco smoking and schizophrenia remains largely unclear. In this study, we conducted a pathway and network analysis on the genes potentially associated with nicotine addiction or schizophrenia to reveal the functional feature of these genes and their interactions. Of the 276 genes associated with nicotine addiction and 331 genes associated with schizophrenia, 52 genes were shared. From these genes, 12 significantly enriched pathways associated with both diseases were identified. These pathways included those related to synapse function and signaling transduction, and drug addiction. Further, we constructed a nicotine addiction-specific and schizophrenia-specific sub-network, identifying 11 novel candidate genes potentially associated with the two diseases. Finally, we built a schematic molecular network for nicotine addiction and schizophrenia based on the results of pathway and network analysis, providing a systematic view to understand the relationship between these two disorders. Our results illustrated that the biological processes underlying the comorbidity of nicotine addiction and schizophrenia was complex, and was likely induced by the dysfunction of multiple molecules and pathways

Analyzing the pathways enriched in genes associated with nicotine dependence in the context of human protein–protein interaction network

<p>Nicotine dependence is the primary addictive stage of cigarette smoking. Although a lot of studies have been performed to explore the molecular mechanism underlying nicotine dependence, our understanding on this disorder is still far from complete. Over the past decades, an increasing number of candidate genes involved in nicotine dependence have been identified by different technical approaches, including the genetic association analysis. In this study, we performed a comprehensive collection of candidate genes reported to be genetically associated with nicotine dependence. Then, the biochemical pathways enriched in these genes were identified by considering the gene’s propensity to be related to nicotine dependence. One of the most widely used pathway enrichment analysis approach, over-representation analysis, ignores the function non-equivalence of genes in candidate gene set and may have low discriminative power in identifying some dysfunctional pathways. To overcome such drawbacks, we constructed a comprehensive human protein–protein interaction network, and then assigned a function weighting score to each candidate gene based on their network topological features. Evaluation indicated the function weighting score scheme was consistent with available evidence. Finally, the function weighting scores of the candidate genes were incorporated into pathway analysis to identify the dysfunctional pathways involved in nicotine dependence, and the interactions between pathways was detected by pathway crosstalk analysis. Compared to conventional over-representation-based pathway analysis tool, the modified method exhibited improved discriminative power and detected some novel pathways potentially underlying nicotine dependence. In summary, we conducted a comprehensive collection of genes associated with nicotine dependence and then detected the biochemical pathways enriched in these genes using a modified pathway enrichment analysis approach with function weighting score of candidate genes integrated. Our results may provide insight into the molecular mechanism underlying nicotine dependence.</p

Cryoablation of cardiophrenic angle lymph node metastases: a case report

Abstract Background Cardiophrenic angle lymph node metastases are relatively rare. Surgical resection is the main treatment for cardiophrenic angle lymph node metastasis, but it is not always possible. Case presentation Here, we report our initial experience with cryoablation of a cardiophrenic angle lymph node metastasis from liver cancer. As the cardiophrenic angle lymph node metastasis was located close to the heart, about 200 mL of 0.9% saline was injected into the pericardium to separate the heart from the target area. The cardiophrenic angle lymph node metastasis was successfully ablated, without any complications. Conclusions Cryoablation may be a suitable alternative treatment for cardiophrenic angle lymph node metastasis

Monitoring of blood pressure.

Background and purposePrevious studies demonstrated that elevated brain natriuretic peptide (BNP) level is associated with adverse clinical outcomes of acute cerebral infarction (ACI). Researchers hypothesized that BNP might be a potential neuroprotective factor against cerebral ischemia because of the antagonistic effect of the natriuretic peptide system on the renin-angiotensin system and regulation of cardiovascular homeostasis. However, whether decreasing the BNP level can improve the prognosis of ACI has not been studied yet. The main effect of sacubitril/valsartan is to enhance the natriuretic peptide system. We investigated whether the intervention of plasma BNP levels with sacubitril/valsartan could improve the prognosis of patients with ACI.MethodsIn a randomized, controlled, parallel-group trial of patients with ACI within 48 hours of symptom onset and need for antihypertensive therapy, patients have randomized within 24 hours to sacubitril/valsartan 200mg once daily (the intervention group) or to conventional medical medication (the control group). The primary outcome was a change in plasma BNP levels before and after sacubitril/valsartan administration. The secondary outcomes included plasma levels of brain-derived neurotrophic factor (BDNF), Corin and neprilysin (NEP) before and after medication, the modified Rankin scale, and the National Institutes of Health Stroke Scale (at onset, at discharge, 30 days, and 90 days after discharge).ResultsWe evaluated 80 eligible patients admitted to the Stroke Center of Lianyungang Second People’s Hospital between 1st May, 2021 and 31st June, 2022. Except for 28 patients excluded before randomization and 14 patients who did not meet the criteria or dropped out or lost to follow-up during the trial, the remaining 38 patients (intervention group: 17, control group: 21) had well-balanced baseline features. In this trial, we found that plasma BNP levels (P = 0.003) decreased and NEP levels (P = 0.006) increased in enrolled patients after treatment with sacubitril/valsartan. There were no differences in plasma BDNF and Corin levels between the two groups. Furthermore, no difference in functional prognosis was observed between the two groups (all P values>0.05).ConclusionsSacubitril/valsartan reduced endogenous plasma BNP levels in patients with ACI and did not affect their short-term prognosis.</div

Fluctuations in systolic blood pressure.

Background and purposePrevious studies demonstrated that elevated brain natriuretic peptide (BNP) level is associated with adverse clinical outcomes of acute cerebral infarction (ACI). Researchers hypothesized that BNP might be a potential neuroprotective factor against cerebral ischemia because of the antagonistic effect of the natriuretic peptide system on the renin-angiotensin system and regulation of cardiovascular homeostasis. However, whether decreasing the BNP level can improve the prognosis of ACI has not been studied yet. The main effect of sacubitril/valsartan is to enhance the natriuretic peptide system. We investigated whether the intervention of plasma BNP levels with sacubitril/valsartan could improve the prognosis of patients with ACI.MethodsIn a randomized, controlled, parallel-group trial of patients with ACI within 48 hours of symptom onset and need for antihypertensive therapy, patients have randomized within 24 hours to sacubitril/valsartan 200mg once daily (the intervention group) or to conventional medical medication (the control group). The primary outcome was a change in plasma BNP levels before and after sacubitril/valsartan administration. The secondary outcomes included plasma levels of brain-derived neurotrophic factor (BDNF), Corin and neprilysin (NEP) before and after medication, the modified Rankin scale, and the National Institutes of Health Stroke Scale (at onset, at discharge, 30 days, and 90 days after discharge).ResultsWe evaluated 80 eligible patients admitted to the Stroke Center of Lianyungang Second People’s Hospital between 1st May, 2021 and 31st June, 2022. Except for 28 patients excluded before randomization and 14 patients who did not meet the criteria or dropped out or lost to follow-up during the trial, the remaining 38 patients (intervention group: 17, control group: 21) had well-balanced baseline features. In this trial, we found that plasma BNP levels (P = 0.003) decreased and NEP levels (P = 0.006) increased in enrolled patients after treatment with sacubitril/valsartan. There were no differences in plasma BDNF and Corin levels between the two groups. Furthermore, no difference in functional prognosis was observed between the two groups (all P values>0.05).ConclusionsSacubitril/valsartan reduced endogenous plasma BNP levels in patients with ACI and did not affect their short-term prognosis.</div

Evolution of mRS scores over time in the two groups.

Evolution of mRS scores over time in the two groups.</p