Abstract-In diffusion-based molecular communication (MC), the most common modulation technique is based on the concentration of information molecules. However, the random delay of molecules due to the channel with memory causes severe inter-symbol interference (ISI) among consecutive signals. In this paper, we propose a detection technique for demodulating signals, the increase detection algorithm (IDA), to improve the reliability of concentration-encoded diffusion-based molecular communication. The proposed IDA detects an increase (i.e., a relative concentration value) in molecule concentration to extract the information instead of detecting an absolute concentration value. To validate the availability of IDA, we establish a real physical tabletop testbed. And we evaluate the proposed demodulation technique using bit error rate (BER) and demonstrate by the tabletop molecular communication platform that the proposed IDA successfully minimizes and even isolates ISI so that a lower BER is achieved than the common demodulation technique.

Diffusion-based and neural communication are two interesting domains in molecular communication. Both of them have distinct advantages and are exploited separately in many works. However, in some cases, neural and diffusion-based ways have to work together for a communication. Therefore, in this paper, we propose a hybrid communication system, in which the diffusion-based and neural communication channels are contained. Multiple connection nano-devices (CND) are used to connect the two channels. We define the practice function of the CNDs and develop the mechanism of exchanging information from diffusion-based to neural channel, based on the biological characteristics of the both channels. In addition, we establish a brief mathematical model to present the complete communication process of the hybrid system. The information exchange process at the CNDs is shown in the simulation. The bit error rate (BER) indicator is used to verify the reliability of communication. The result reveals that based on the biological channels, optimizing some parameters of nano-devices could improve the reliability performance.

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SARS-CoV-2 is the causative agent for the global COVID-19 pandemic; however, the interaction between virus and host is not well characterized. Natural killer cells play a key role in the early phase of the antiviral response, and their primary functions are dependent on signaling through the killer cell immunoglobulin-like receptor (KIR). This study measured the association between KIR/HLA class I ligand pairings and the occurrence and development of COVID-19. DNA of blood samples from 257 COVID-19 patients were extracted and used to detect KIR and HLA-C gene frequencies using single strain sequence-specific primer (SSP) PCR. The frequency of these genes was compared among 158 individuals with mild COVID-19, 99 with severe disease, and 98 healthy controls. The frequencies of KIR2DL2 (P=0.04, OR=1.707), KIR2DS3 (P=0.047, OR=1.679), HLA-C1C1 (P<0.001, OR=3.074) and the KIR2DL2/HLA-C1C1 pairing (P=0.038, OR=2.126) were significantly higher in the COVID-19 patients than the healthy controls. At the same time, the frequency of KIR2DL3+KIR2DL2-/HLA-C1+Others+ was lower in COVID-19 patients than in healthy individuals (P=0.004, OR=0.477). These results suggest that the protective effect of KIR2DL3 against SARS-CoV-2 infection is related to the absence of the KIR2DL2 gene. This study found no correlation between the frequencies of these genes and COVID-19 pathogenesis. Global statistical analysis revealed that the incidence of COVID-19 infection was higher in geographic regions with a high frequency of KIR2DL2. Together these results suggest that the KIR2DL2/HLA-C1C1 gene pairing may be a risk factor for SARS-CoV-2 infection.