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Next-generation sensor and radio access networks (NG-SRANs) namely, Hydra radio access networks (H-RANs) represent a significant evolution in the telecommunications and sensor ecosystem landscape in anticipation of 6G deployment and beyond. H-RAN’s vision derives its strength from integrating various technologies and networks into a single central network with the widespread incorporation of artificial intelligence (AI) technologies throughout the network. As a result, H-RAN’s unique features and characteristics can serve as a baseline for innovating new applications and significantly enhance the overall functions of conventional open radio access networks (O-RANs). However, among the many improvements and innovations that the H-RAN architecture promises in its functionality, this paper focuses on the initial access implementation “ $\text {Task}_{1}$ ” approach. Our solution contains several novelties that enhance both overhead and model accuracy. To this end, we define a novel intelligent perception network inspired by the knowledge distribution idea for collaborative H-RAN networks. We develop sparse multi-task learning (SMTL) as part of the AI/ML D-engine for federated learning to perform multiple tasks simultaneously. The SMTL is designed to select the optimal solution from a list of recommended solutions, namely “Tasks”. In the simulation, figures of merit include metrics such as top-k validation accuracy, beam selection accuracy, throughput ratios, beam sweep time, latency, and initial access times, which are used to evaluate the performance and efficiency of the proposed technologies. Simulation results demonstrate that by exploiting contextual information from distributed collaborative SRUs, and UE sends its own sensing information via a physical random-access channel in addition to using SMTL, our H-RAN-based initial access scheme can achieve 82.9% throughput of an exhaustive beam search (EBS) based-O-RAN network without any beam search overhead and 96.7% by searching among as few as 5 beams. Compared to the conventional MMW 5G-NR solution, our proposed method significantly minimizes the beam search time needed to reach the desired throughput.

After researchers devoted considerable efforts to developing 5G standards, their passion began to focus on establishing the basics for the standardization of 6G and beyond. The utilization of millimeter wave (MMW) and terahertz (THz) frequency bands, combined with sensors and artificial intelligence (AI), has gained significant attention in the research community for the development of the next generation of sensory and radio access networks (NG-SRANs). Leveraging the advantages of communication and sensor systems’ common characteristics will open horizons for merging the two networks, thereby creating a unified perceptive and intelligence network. Overall, while using MMW and THz frequencies is certainly valuable, the ability to gather and transmit data in real-time makes sensors extremely effective in communication networks. In contrast, AI, machine learning (ML), and deep learning (DL) have become predominant methods for solving data analysis problems across a wide range of domains, such as analyzing large amounts of different sensor data, decision-making, channel estimation, self-organization, and self-healing. This paper proposes a novel design for a potential 6G network and beyond called the Hydra radio access network (H-RAN) perceptual networks architecture, which is designed based on NG-SRAN. From a design perspective, H-RAN aims to merge communication and sensing networks into a single network in which two functionalities are attempted to mutually complement each other, namely communication-aided sensing and sensing-aided communications networks. However, such a network provides an adequate platform for a wide range of AL/ML algorithms, such as real-time decision-making, self-organization, and self-healing. As a result, H-RAN perceptual networks architecture is expected to be more efficient, reliable, and secure than existing conventional networks, and is likely to play a critical role in a wide range of applications, including but not limited to mobile broadband, sensing systems, smart cities, autonomous vehicles, the internet of things (IoT) connectivity, vehicle-to-everything (V2X) communication, etc. This study gives a detailed overview of how H-RAN will revolutionize conventional future sensors and cellular networks through a comprehensive analysis of H-RAN architectural components and functionalities.

An edge intelligence-aided Internet-of-Things (IoT) network has been proposed to accelerate the response of IoT services by deploying edge intelligence near IoT devices. The transmission of data from IoT devices to the edge nodes leads to large network traffic in the wireless connections. Federated Learning (FL) is proposed to solve the high computational complexity by training the model locally on IoT devices and sharing the model parameters in the edge nodes. This paper focuses on developing an efficient integration of joint edge intelligence nodes depending on investigating an energy-efficient bandwidth allocation, computing Central Processing Unit (CPU) frequency, optimization transmission power, and the desired level of learning accuracy to minimize the energy consumption and satisfy the FL time requirement for all IoT devices. The proposal efficiently optimized the computation frequency allocation and reduced energy consumption in IoT devices by solving the bandwidth optimization problem in closed form. The remaining computational frequency allocation, transmission power allocation, and loss could be resolved with an Alternative Direction Algorithm (ADA) to reduce energy consumption and complexity at every iteration of FL time from IoT devices to edge intelligence nodes. The simulation results indicated that the proposed ADA can adapt the central processing unit frequency and power transmission control to reduce energy consumption at the cost of a small growth of FL time.

Abstract Dietary antigens affect the adaptive immunity of the host by inducing regulatory T cells and IgE-producing B cells. However, their roles in innate immune compartments such as innate lymphoid cells (ILCs) and intestinal epithelial cells (IECs) are unclear. Here, using antigen-free (AF) mice, which are germ-free (GF) mice fed with amino-acid-based diet, we found dietary proteins suppress the development of GATA-3-expressing ILC2s independent of the adaptive immune cells. These cells produce more type 2 cytokines and upregulated proliferation and activation markers such as Ki-67, CD69, and CD25. With this, AF mice had increased expressions of tuft cell-specific transcripts such as Il25, Il33, Dclk1, Trpm5, and Pou2f3 in IECs. Accordingly, expanded ILC2s upregulated IL-17RB, a receptor of IL-25, and their proliferation was blocked by IL-25 neutralizing or IL-17RB blocking antibodies. These results suggest a new dialogue between dietary antigens, IECs, and ILCs in which dietary antigens suppress ILC2 activation and proliferation by restraining homeostatic IL-25 production, potentially limiting type 2 immunity by food antigens.

A multi-gigabit (WiGig) system is designed based on IEEE 802.11ad standards by exploiting millimeter-wave (mmWave) bands to achieve extremely high data rates. Recently, IEEE 802.11bd and 3GPP NR-V2X technologies adopted new specifications for the next generation vehicle-to-everything (V2X) network with the ability to support mmWave bands. However, mmWave bands could be the solution for the high throughput and low latency. Still, the instability of blockages is a substantial challenge in mmWave bands, rendering mmWave ineffective in vehicular networks. Typically, technologies capable of operating at mmWave bands, such as IEEE 802.11ad, IEEE 802.11bd, NR-V2X, etc., share the same technical challenges due to the unique characteristics of the mmWave band. As a result, to achieve the aspirations of next generation connected mmWave V2X vehicles. This paper proposes novel classic, cooperative, and extension protocols for IEEE 802.11bd by enhancing IEEE 802.11ad. The proposed solution aims to mitigate some of the most common technical challenges associated with using mmWave bands in V2X networks, such as beam training overhead, link blockage, beam misalignment, limited coverage range, and delay. Simulation results demonstrate that the proposed approach effectively reduces the beam training overhead, achieves accurate beam alignment, increases the probability of line-of-sight (LOS), overcomes link blockage/ misalignment, extends the coverage range, and achieves low latency. Further, the proposed enhancement achieves significantly higher performance against the conventional solution and shows more link stability despite continuous changes in the density of the vehicles.

The convergence of Artificial Intelligence (AI) can overcome the complexity of network defects and support a sustainable and green system. AI has been used in the Cognitive Internet of Things (CIoT), improving a large volume of data, minimizing energy consumption, managing traffic, and storing data. However, improving smart packet transmission scheduling (TS) in CIoT is dependent on choosing an optimum channel with a minimum estimated Packet Error Rate (PER), packet delays caused by channel errors, and the subsequent retransmissions. Therefore, we propose a Generative Adversarial Network and Deep Distribution Q Network (GAN-DDQN) to enhance smart packet TS by reducing the distance between the estimated and target action-value particles. Furthermore, GAN-DDQN training based on reward clipping is used to evaluate the value of each action for certain states to avoid large variations in the target action value. The simulation results show that the proposed GAN-DDQN increases throughput and transmission packet while reducing power consumption and Transmission Delay (TD) when compared to fuzzy Radial Basis Function (fuzzy-RBF) and Distributional Q-Network (DQN). Furthermore, GAN-DDQN provides a high rate of 38 Mbps, compared to actor-critic fuzzy-RBF’s rate of 30 Mbps and the DQN algorithm’s rate of 19 Mbps.

Ultra-reliable and Low-latency Communications (URLLC) is expected to be one of the most critical characteristics Beyond fifth-Generation (B5G) cellular networks with stringent low latency and high-reliability requirements. The Deep Reinforcement Learning (deep-RL) framework has been applied to predict the optimization of a Resource Block (RB) and minimize Power Allocation (PA) to guarantee a high End-to-End (E2E) reliability and low E2E latency under rate constraints. This paper proposes a novel Policy Gradient-based Actor-Critic Learning (PGACL) algorithm to optimize the policy gradient for optimal rate allocation to solve the RB, minimize power, and guarantee a solution for URLLC scheduling. The purpose of a PGACL algorithm is to provide a good policy with a closer convergence rate and a low computational cost depending on the reduced action space for every user. URLLC systems need to operate in highly reliable systems and account for extreme network conditions. Therefore, we proposed the refiner Generative Adversarial Networks (GANs) that apply enough extreme events for the deep-RL agent to generate synthetic data with high reliability similar to real data based on the regulated number of extreme events in the dataset. This refiner GAN method enables a deep-RL approach to generate large amounts of data practically used in real-time operations. Simulation results showed that the proposed deep-RL for refiner-GAN can omit the transient training time and develop deep learning based on a controlled set of unlabeled real traffic at a relatively short time. Furthermore, the refiner GAN demonstrated 99.9999% reliability and E2E latency of less than 1.4ms.

The gut microbiota plays an important role in regulating the host immune systems. It is well established that various commensal microbial species can induce the differentiation of CD4+ T helper subsets such as Foxp3+ regulatory T (Treg) cells and Th17 cells in antigen-dependent manner. The ability of certain microbial species to induce either Treg cells or Th17 cells is often linked to the altered susceptibility to certain immune disorders that are provoked by aberrant T cell response against self-antigens. These findings raise an important question as to how gut microbiota can regulate T cell repertoire and the activation of autoreactive T cells. This review will highlight microbiota-dependent regulation of thymic T cell development, maintenance of T cell repertoire in the secondary lymphoid tissues and the intestine, and microbiota-mediated modulation of autoreactive and tumor neoantigen-specific T cells in autoimmune diseases and tumors, respectively.

Yeast form part of the host microbiome with known impact on host immunity. Here the authors identify and investigate the impact of commensal yeast-derived polysaccharides in modulating host inflammation, and show its potential for inhibiting inflammation in a number of models of inflammatory diseases.

Under steady-state conditions, conventional CD4+ T lymphocytes are classically divided into naïve (CD44lo CD62Lhi) and memory (CD44hi CD62Llo) cell compartments. While the latter population is presumed to comprise a mixture of distinct subpopulations of explicit foreign antigen (Ag)-specific “authentic” memory and foreign Ag-independent memory-phenotype (MP) cells, phenotypic markers differentially expressed in these two cell types have yet to be identified. Moreover, while MP cells themselves have been previously described as heterogeneous, it is unknown whether they consist of distinct subsets defined by marker expression. In this study, we demonstrate using combined single-cell RNA sequencing and flow cytometric approaches that self-driven MP CD4+ T lymphocytes are divided into CD127hi Sca1lo, CD127hi Sca1hi, CD127lo Sca1hi, and CD127lo Sca1lo subpopulations that are Bcl2lo, while foreign Ag-specific memory cells are CD127hi Sca1hi Bcl2hi. We further show that among the four MP subsets, CD127hi Sca1hi lymphocytes represent the most mature and cell division-experienced subpopulation derived from peripheral naïve precursors. Finally, we provide evidence arguing that this MP subpopulation exerts the highest responsiveness to Th1-differentiating cytokines and can induce colitis. Together, our findings define MP CD4+ T lymphocytes as a unique, self-driven population consisting of distinct subsets that differ from conventional foreign Ag-specific memory cells in marker expression and establish functional relevance for the mature subset of CD127hi Sca1hi MP cells.

CD4+ T cells contain a T-bethigh memory-phenotype (MP) population with innate-like functions. Here the authors characterize the requirements for their differentiation at homeostasis and identify a function for IL-12 that is tonically produced by type 1 dendritic cells in an MyD88- and CD40-dependent, but foreign PAMP-independent manner.

It is a challenging task to design a random access protocol that achieves the optimal throughput in multi-cell random access with decentralized transmission due to the difficulty of coordination. In this paper, we present a decentralized interference-aware opportunistic random access (IA-ORA) protocol that enables us to obtain the optimal throughput scaling in an ultra-dense multi-cell random access network with one access point (AP) and a number of users. In sharp contrast to opportunistic scheduling for cellular multiple access where users are selected by base stations, under the IA-ORA protocol, each user opportunistically transmits with a predefined physical layer (PHY) data rate in a decentralized manner if not only the desired signal power to the serving AP is sufficiently large but also the generating interference leakage power to the other APs is sufficiently small (i.e., two threshold conditions are fulfilled). As a main result, it is shown that the optimal aggregate throughput scaling (i.e., the MAC throughput of e/1 in a cell and the power gain) is achieved in a high signal-to-noise ratio regime if the number of per-cell users exceeds some level. Additionally, it is numerically demonstrated via computer simulations that under practical settings, the proposed IA-ORA protocol outperforms conventional opportunistic random access protocols in terms of aggregate throughput.

Multiuser hybrid precoding in 5G NR mmWave communication system faces significant challenges such as establishing accurate directional radio links and maintaining links for mobile stations (MSs) moving in outdoor environments. A conventional solution relies on finite codebook-based beam sweeping for initial first-stage beam acquisition and subsequent second-stage beam tracking by sweeping adjacent beam pairs. However, such a conventional solution has inevitable residual AoA/AoD errors even after the best beam pair is established in the first stage and incurs nonnegligible overheads to sound adjacent beam pairs for maintaining the best beam pair in the second stage. To overcome these problems, a novel codebook-based two-stage solution that combines a novel beam tracking protocol with a low sounding overhead, a unique receiver structure employing a beam scheduler and a beam tester, and a fine accuracy residual AoA/AoD error estimation algorithm based on the monopulse ratio concept is proposed. The solution is unique because of the receiver structure for the residual AoA/AoD error estimation that exploits the cyclic prefix in OFDM systems, inspired by the monopulse ratio in radar systems. Moreover, it can be applied to MSs with a single RF chain. This solution, using the proposed receiver structure and algorithm, can establish a more accurate directional beam pair right after the initial beam sweeping in the first stage. For beam tracking in the second stage, it estimates the residual AoA/AoD errors of the current best beam pair rather than sweeping adjacent beam pairs, thereby reducing beam tracking overheads. Numerical evaluation and computer simulations show that the proposed solution offers more accurate beam acquisition (i.e., average array gain improvement of several dB) and costs considerably reduced beam sounding overheads compared to the conventional solution. Lastly, a ray-tracing tool is used to demonstrate that our solution is effective in practical channel parameters for outdoor environments.

The intestine harbors a complex community of bacterial species collectively known as commensal microbiota. Specific species of resident bacteria, as known as pathobiont, have pathogenic potential and can induce apparent damage to the host and intestinal inflammation in a certain condition. However, the host immune factors that permit its commensalism under steady state conditions are not clearly understood. Here, we studied the gut fitness of Listeria monocytogenes by using germ-free (GF) mice orally infected with this food-borne pathogen. L. monocytogenes persistently exists in the gut of GF mice without inducing chronic immunopathology. L. monocytogenes at the late phase of infection is not capable of infiltrating through the intestinal barrier. L. monocytogenes established the commensalism through the reversible down regulation of virulence gene expression. CD8+ T cells were found to be sufficient for the commensalism of L. monocytogenes. CD8+ T cells responding to L. monocytogenes contributed to the down-regulation of virulence gene expression. Our data provide important insights into the host-microbe interaction and have implications for developing therapeutics against immune disorders induced by intestinal pathogens or pathobionts.

Summary: The complement fragment C5a is closely associated with adaptive immune induction in the mucosa. However, the mechanisms that control CD8+ T cell responses by C5a have not been extensively explored. This study reveals that C5/C5a in the Peyer’s patch (PP) subepithelial dome increases upon oral Listeria infection. We hypothesize that C5aR+ PP cells play an important role in the induction of antigen-specific T cell immunity. Using single-cell RNA sequencing, we identify C5aR- and lysozyme-expressing dendritic cells (C5aR+ LysoDCs) in PP and examine their role in CD8+ T cell immune induction. Stimulation of C5aR+ LysoDCs by C5a increases reactive oxygen species levels, leading to efficient antigen cross-presentation, which elicits an antigen-specific CD8+ T cell response. In C5-deficient mice, oral co-administration of C5a and Listeria enhances Listeria-specific cytotoxic T cell levels. Collectively, these findings suggest a role of the complement system in intestinal T cell immunity.

Mucin-degrading bacteria are densely populated in the intestinal epithelium; however, their interaction with intestinal stem cells (ISCs) and their progeny have not been elucidated. To determine whether mucin-degrading bacteria play a role in gut homeostasis, mice were treated with Akkermansia muciniphila, a specialized species that degrades mucin. Administration of A. muciniphila for 4 weeks accelerated the proliferation of Lgr5+ ISCs and promoted the differentiation of Paneth cells and goblet cells in the small intestine (SI). We found similar effects of A. muciniphila in the colon. The levels of acetic and propionic acids were higher in the cecal contents of A. muciniphila-treated mice than in PBS-treated mice. SI organoids treated with cecal contents obtained from A. muciniphila-treated mice were larger and could be diminished by treatment with G protein-coupled receptor (Gpr) 41/43 antagonists. Pre-treatment of mice with A. muciniphila reduced gut damage caused by radiation and methotrexate. Further, a novel isotype of the A. muciniphila strain was isolated from heathy human feces that showed enhanced function in intestinal epithelial regeneration. These findings suggest that mucin-degrading bacteria (e.g., A. muciniphila) may play a crucial role in promoting ISC-mediated epithelial development and contribute to intestinal homeostasis maintenance.

Retinal dehydrogenase (RALDH) enzymatic activities catalyze the conversion of vitamin A to its metabolite Retinoic acid (RA) in intestinal dendritic cells (DCs) and promote immunological tolerance. However, precise understanding of the exogenous factors that act as initial trigger of RALDH activity in these cells is still evolving. By using germ-free (GF) mice raised on an antigen free (AF) elemental diet, we find that certain components in diet are critically required to establish optimal RALDH expression and activity, most prominently in small intestinal CD103+CD11b+ DCs (siLP-DCs) right from the beginning of their lives. Surprisingly, systematic screens using modified diets devoid of individual dietary components indicate that proteins, starch and minerals are dispensable for this activity. On the other hand, in depth comparison between subtle differences in dietary composition among different dietary regimes reveal that adequate glucose concentration in diet is a critical determinant for establishing RALDH activity specifically in siLP-DCs. Consequently, pre-treatment of siLP-DCs, and not mesenteric lymph node derived MLNDCs with glucose, results in significant enhancement in the in vitro generation of induced Regulatory T (iTreg) cells. Our findings reveal previously underappreciated role of dietary glucose concentration in establishing regulatory properties in intestinal DCs, thereby extending a potential therapeutic module against intestinal inflammation.

The primary induction sites for intestinal IgA are the gut-associated lymphoid tissues (GALT), such as Peyer's patches (PPs) and isolated lymphoid follicles (ILFs). The commensal microbiota is known to contribute to IgA production in the gut; however, the role of dietary antigens in IgA production is poorly understood. To understand the effect of dietary antigens on IgA production, post-weaning mice were maintained on an elemental diet without any large immunogenic molecules. We found that dietary antigens contribute to IgA production in PPs through induction of follicular helper T cells and germinal center B cells. The role of dietary antigens in the PP responses was further confirmed by adding bovine serum albumin (BSA) into the elemental diet. Although dietary antigens are important for PP responses, they have fewer effects than the microbiota on the development and maturation of ILFs. Furthermore, we demonstrated that dietary antigens are essential for a normal antigen-specific IgA response to Salmonella typhi serovar Typhimurium infection. These results provide new insights into the role of dietary antigens in the regulation of mucosal immune responses.

Signal occlusion by building blockages is a double-edged sword for the performance of millimeter-wave (mmW) communication networks. Buildings may dominantly attenuate the useful signals, especially when mmW base stations (BSs) are sparsely deployed compared with the building density. In the opposite BS deployment, buildings can block the undesired interference. To enjoy only the benefit, we propose a building-aware association scheme that adjusts the directional BS association bias of the user equipments (UEs), based on a given building density and the concentration of UE locations around the buildings. The association of each BS can thereby be biased: 1) toward the UEs located against buildings for avoiding interference to other UEs or 2) toward the UEs providing their maximum reference signal received powers. The proposed association scheme is optimized to maximize the downlink average data rate derived by stochastic geometry. Its effectiveness is validated by simulation using real building statistics.

Device to device (D2D) communication brings numerous benefits for future heterogeneous cellular networks. However, an energy-efficient design of such D2D communications is a critical challenge due to the cochannel deployment and limited power of users. In this paper, we present an energy-efficient self-organized cross-layer optimization scheme, which aims to maximize the D2D communication energy-efficiency without jeopardizing the quality of service (QoS) requirements of other tiers. Specifically, we model the cross-layer optimization, which includes resource block (RB) and power allocation using a noncooperative game. In the proposed scheme, each D2D transmitter user, which is a player in the game, operates in a self-organizing manner and selects the RBs and the power levels for enhancing its energy efficiency while maintaining the QoS requirements of other heterogeneous parties. Concerning the computationally intense nature of the global optimization problem, we decompose the problem into two subproblems: the RB allocation and the power allocation, and solve them iteratively in a game-theoretic manner. Simulation results demonstrate superior energy efficiency performance of the proposed scheme over conventional schemes. In addition, it is also shown via simulation that the performance of the proposed scheme degrades if the channel state information is not precisely available.

In this paper, the uplink semi-persistent scheduling policy problem of minimizing network latency is considered for a training-based large-scale antenna system employing two simple linear receivers, a maximum ratio combiner and a zero-forcing receiver, while satisfying each user's reliability and latency constraints under an energy constraint. The network latency is defined as the air-time requested either to serve all users with a minimum quality-of-service, including reliability constraints and minimum throughput levels, or to maximize the spectral efficiency. Optimal non-orthogonal pilots are used to decrease the network latency. An optimization algorithm for determining the latency-optimal uplink scheduling policy using binary-integer programming (BIP) with an exponential-time complexity is proposed. In addition, it is proven that a linear programming relaxation of the BIP can provide an optimal solution with a polynomial-time complexity. Numerical simulations demonstrate that the proposed scheduling policy can provide several times lower network latency in realistic environments than conventional policies. The proposed optimal semi-persistent scheduling policy provides critical guidelines for designing 5G and future cellular systems, particularly for their ultra-reliable low-latency communication services.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

The fast and intense proliferative responses have been well documented for naïve T cells adoptively transferred into chronic lymphopenic hosts. This response known as spontaneous proliferation (SP), unlike antigen-independent lymphopenia-induced proliferation (LIP), is driven in a manner dependent on antigens derived from commensal microbiota. However, the precise nature of the SP response and its impact on homeostasis and function for T cells rapidly responding under this lymphopenic condition are still unclear. Here we demonstrate that, when naïve T cells were adoptively transferred into specific pathogen-free (SPF) but not germ-free (GF) RAG−/− hosts, the SP response of these cells substantially affects the intensity and tempo of the responding T cells undergoing LIP. Therefore, the resulting response of these cells in SPF RAG−/− hosts was faster and stronger than the typical LIP response observed in irradiated B6 hosts. Although the intensity and tempo of such augmented LIP in SPF RAG−/− hosts were analogous to those of antigen-dependent SP, the former was independent of antigenic stimulation but most importantly, dependent on IL-2. Similar observations were also apparent in other acute lymphopenic settings where antigen-dependent T cell activation can strongly occur and induce sufficient levels of IL-2 production. Consequently, the resulting T cells undergoing IL-2-driven strong proliferative responses showed the ability to differentiate into functional effector and memory cells that can control infectious pathogens. These findings therefore reveal previously unappreciated role of IL-2 in driving the intense form of T cell proliferative responses in chronic lymphopenic hosts.

We have previously generated a mouse model of spontaneous Th2-associated disease of the small intestine called TRAF6ΔDC, in which dendritic cell (DC)-intrinsic expression of the signaling mediator TRAF6 is ablated. Interestingly, broad-spectrum antibiotic treatment ameliorates TRAF6ΔDC disease, implying a role for commensal microbiota in disease development. However, the relationship between the drug effects and commensal microbiota status remains to be formally demonstrated. To directly assess this relationship, we have now generated TRAF6ΔDC bone marrow chimera mice under germ-free (GF) conditions lacking commensal microbiota, and found, unexpectedly, that Th2-associated disease is actually exacerbated in GF TRAF6ΔDC mice compared to specific pathogen-free (SPF) TRAF6ΔDC mice. At the same time, broad-spectrum antibiotic treatment of GF TRAF6ΔDC mice has an ameliorative effect similar to that observed in antibiotics-treated SPF TRAF6ΔDC mice, implying a commensal microbiota-independent effect of broad-spectrum antibiotic treatment. We further found that treatment of GF TRAF6ΔDC mice with broad-spectrum antibiotics increases Foxp3+ Treg populations in lymphoid organs and the small intestine, pointing to a possible mechanism by which treatment may directly exert an immunomodulatory effect. To investigate links between the exacerbated phenotype of the small intestines of GF TRAF6ΔDC mice and local microbiota, we performed microbiotic profiling of the luminal contents specifically within the small intestines of diseased TRAF6ΔDC mice, and, when compared to co-housed control mice, found significantly increased total bacterial content characterized by specific increases in Firmicutes Lactobacillus species. These data suggest a protective effect of Firmicutes Lactobacillus against the spontaneous Th2-related inflammation of the small intestine of the TRAF6ΔDC model, and may represent a potential mechanism for related disease phenotypes.