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More than 250 million people are living with chronic hepatitis B despite the availability of highly effective vaccines and oral antivirals. Although innate and adaptive immune cells play crucial roles in controlling hepatitis B virus (HBV) infection, they are also accountable for inflammation and subsequently cause liver pathologies. During the initial phase of HBV infection, innate immunity is triggered leading to antiviral cytokines production, followed by activation and intrahepatic recruitment of the adaptive immune system resulting in successful virus elimination. In chronic HBV infection, significant alterations in both innate and adaptive immunity including expansion of regulatory cells, overexpression of co-inhibitory receptors, presence of abundant inflammatory mediators, and modifications in immune cell derived exosome release and function occurs, which overpower antiviral response leading to persistent viral infection and subsequent immune pathologies associated with disease progression towards fibrosis, cirrhosis, and hepatocellular carcinoma. In this review, we discuss the current knowledge of innate and adaptive immune cells transformations that are associated with immunopathogenesis and disease outcome in CHB patients.

[This corrects the article DOI: 10.3389/fimmu.2025.1671149.].

Epilepsy is a nervous system disorder. Encephalography (EEG) is a generally utilized clinical approach for recording electrical activity in the brain. Although there are a number of datasets available, most of them are imbalanced due to the presence of fewer epileptic EEG signals compared with non-epileptic EEG signals. This research aims to study the possibility of integrating local EEG signals from an epilepsy center in King Abdulaziz University hospital into the CHB-MIT dataset by applying a new compatibility framework for data integration. The framework comprises multiple functions, which include dominant channel selection followed by the implementation of a novel algorithm for reading XLtek EEG data. The resulting integrated datasets, which contain selective channels, are tested and evaluated using a deep-learning model of 1D-CNN, Bi-LSTM, and attention. The results achieved up to 96.87% accuracy, 96.98% precision, and 96.85% sensitivity, outperforming the other latest systems that have a larger number of EEG channels.

This paper presents a method for switching reduction in cascaded H-bridge converters. Given the wide applicability of this topology, it would be especially desirable to increase its efficiency with switching losses reduction techniques. Since this type of converter requires voltage balancing methods, several modulation methods consider the possibility of combining the balancing and switching reduction goals together. In this paper, a previously disclosed optimization-based balance method was modified further to consider the switching losses in its objective function. Each commutation was penalized in proportion to the phase current and the module voltage, thus avoiding commutations that would produce the most losses but tolerating low-losses commutations. The structure of the original method was maintained so that the algorithm could be applied with minimal change. The results show that it is possible to reduce the switching up to 14% without any noticeable drawback and up to 22% at the cost of a greater DC-link ripple. It is also possible to selectively reduce the effective switching frequency of only some modules, making it significantly low. This extends the adaptability of the converter, possibly allowing hybrid converters with modules of different transistor technologies.

This paper proposes a new cascaded multilevel converter topology based on three-phase H bridge cells with a common DC-link structure. The proposed multilevel converter topology main advantages, compared with literature renowned multilevel converters topologies, are discussed in the paper, such as modularity, construction, implementation cost, and DC voltage ripple mitigation. Despite presenting an elementary structure and easy implementation, the use of classic PWM switching strategies is not feasible for this topology, causing the appearance of several short-circuit states between its capacitors. Thus, a graph theory algorithm combined with a model predictive control is also proposed in this work to identify and avoid the new cascaded multilevel converter short-circuit switching states and, concomitantly, guaranteeing the converter output power quality. In order to validate the presented topology applicability, a low voltage synchronous static compensators (STATCOM) with an optimal switching vector model predictive control (OSV-MPC) is implemented in a hardware-in-the-loop platform. The real-time experimental results prove the proposed multilevel topology and the OSV-MPC control strategy effectiveness.

Numerous cascaded inverter configurations have been developed to generate higher voltage levels, thereby improving performance and lowering costs. Comparing conventional delta-connected cascaded H-bridge (CHB) multilevel inverters to star-connected CHB multilevel inverters reveals a disadvantage. In conventional delta-connected CHB multilevel inverters, more switches are unavoidably needed to achieve the same line-to-line grid voltage, since more H-bridges cascaded in series are required than in a star-connected CHB. This paper presents a modified topology based on the delta-connected CHB multilevel configuration to provide the same number of line-to-line voltage levels as a star-connected CHB, using an equivalent number of switches. The number of switches in the proposed multilevel inverter is decreased compared to conventional delta-connected CHB MLIs at the same voltage levels. The mathematical modeling of the proposed topology and the simulation results using a fixed load and a PV-grid connection are provided to validate the efficacy and dependability of the proposed topology. To validate the usefulness of the proposed configuration, it was practically implemented in the laboratory. Data acquisition and generation of gating signals to fire the switches were implemented using a MicroLabBox real-time controller. The prototype was examined under a resistive–inductive load and tested under different modulation indices. To demonstrate the effectiveness and the functionality of the topology, the experimental results are also provided.

Hepatitis D virus (HDV) infection affects more than 10 million people worldwide, with an estimated prevalence of nearly 4.5% among HBsAg-positive individuals. Epidemiological studies have shown a significant increase in the prevalence of hepatocellular carcinoma (HCC) in patients with chronic HDV infection compared to those with chronic hepatitis B virus (HBV) mono-infection. Despite the clinical findings, data on molecular oncogenic mechanisms are limited and fragmentary. Moreover, the role of HDV in promoting the development of HCC has so far been controversial, because it is difficult to weigh the respective contributions of the two viruses. In this review, we focused on the direct oncogenic action of HDV, its role in modifying the tumor microenvironment, and the genetic signature of HDV-related HCC, comparing these features with HBV-related HCC.

In this study, fault-tolerant operation of multilevel cascaded H-bridge (CHB) inverters is presented and a novel switching strategy based on space vector modulation is proposed. A faulty power switch in high power converters can lead to expensive downtime, loss of productivity and increased costs. Various power switch faults and their influence on space vector diagram of CHB inverters are investigated. In the event of a fault, the output voltage of inverter is reduced and redundant switching states are used to generate balanced line-to-line voltages. By adding some devices to the basic structure, CHB inverter will operate with maximum achievable output voltage. Simulation and experimental results are shown for a five-level CHB inverter to validate the proposed modulation technique.