Gut microbial and clinical characteristics of individuals with autism spectrum disorder differ depending on the ecological structure of the gut microbiome.

Understanding the relationship between the gut microbiome and autism spectrum disorder (ASD) is challenging due to the heterogeneous nature of ASD. Here, we analyzed the microbial and clinical characteristics of individuals with ASD using enterotypes. A total of 456 individuals participated in the study, including 249 participants with ASD, 106 typically developing siblings, and 101 controls. The alpha and beta diversities of the ASD, sibling, and control groups did not show significant differences. Analysis revealed a negative association between the Bifidobacterium longum group and the Childhood Autism Rating Scale, as well as a negative association between the Streptococcus salivarus group and the Social Responsiveness Scale (SRS) within the ASD group. When clustered based on microbial composition, participants with ASD exhibited two distinct enterotypes, E1 and E2. In the E2 group, the SRS score was significantly higher, and the Vineland Adaptive Behavior Scale score was significantly lower compared to the E1 group. Machine learning results indicated that the microbial species predicting SRS scores were distinct between the two enterotypes. Our study suggests that the microbial composition in individuals with ASD exhibits considerable variability, and the patterns of associations between the gut microbiome and clinical symptoms may vary depending on the enterotype.

Longitudinal associations between gut microbiome diversity and emotional well-being.

OBJECTIVE: While a significant link between emotional well-being (EWB) and the gut microbiome has been reported recently, their temporal relationships remain elusive. This study aims to fill this gap by examining the longitudinal associations between EWB and the Shannon Index (SI), an indicator of gut microbiome diversity. METHOD: The analysis focused on a dataset that collected participants' current EWB and fecal samples in both 2019 and 2022 (N = 57, 56.1% female, Mage = 52.47 years, SD = 12.65). Gut microbiome profiles were generated by sequencing the 16S rRNA gene, from which SI was subsequently calculated. RESULTS: The cross-lagged panel analysis revealed significant positive cross-sectional associations between EWB and SI in both 2019 (ß = .296, SE = 0.121, p = .014) and 2022 (ß = .324, SE = 0.119, p = .006). However, no significant longitudinal associations were found between 2019 EWB and 2022 SI (ß = .068, SE = 0.138, p = .623), nor between 2019 SI and 2022 EWB (ß = -.016, SE = 0.13, p = .899). CONCLUSIONS: Our findings indicate that emotional happiness may be associated with gut microbiome profiles at a particular time point, but they may not serve as predictive factors for each other over time. Future research is needed to establish causal relationships between them. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Gut microbial signatures in clinically stable ulcerative colitis according to the mucosal state and associated symptoms.

BACKGROUND AND AIM: The gut microbiome of patients with clinically stable ulcerative colitis (UC) differs from that of healthy individuals depending on the state of the colonic mucosa, especially with or without advanced scarring; however, the underlying mechanism is unclear. Therefore, this study examined the gut microbiome compositional signatures in patients with significant mucosal scarring and UC-related symptoms. METHODS: Stool samples for gut microbiome analysis were prospectively collected from 57 patients with clinically stable UC between January 1 and December 31, 2022. Data from 57 individuals without inflammatory bowel disease (non-IBD) paired by age and sex were selected from our previous study as the control group. The fecal samples were subjected to 16S rRNA gene sequencing. Associations between gut microbiome profiles and clinical or colonoscopic assessments were examined using diversity and differential abundance analyses. RESULTS: Gut microbiome compositions between the patients with clinically stable UC and non-IBD controls differed significantly. Furthermore, gut microbiome compositions varied between the preserved and altered mucosa groups identified based on mucosal changes in the UC group. Differential abundance test of patients with UC for symptomatic remission based on stool frequency from the two-item patient-reported outcome identified several overlapping taxa specified as gut microbiome signatures, including the Enterobacteriaceae unknown genera (Enterobacteriaceae_g), Klebsiella, and several Lachnospiraceae spp. both in mucosal and symptom change analyses. CONCLUSIONS: The gut microbiome can change with mucosal changes, even in clinically stable UC, and some gut microbial signatures may explain the symptom manifestations in patients with UC showing significant mucosal changes.

A 5.8 GHz 1.8 V +20 dBm 32.5% PAE Power Amplifier for a Short-Range Over-the-Air WPT Application.

This paper presents a 5.8 GHz differential cascode power amplifier for an over-the-air wireless power transfer application. Over-the-air wireless power transfer provides a variety of benefits in several applications such as the Internet of Things and medical implantation applications. The proposed PA features two fully differentially active stages with a custom-designed transformer to provide a single-ended output. The custom-made transformer shows a high quality factor, as high as 11.6 and 11.2 for the primary and secondary sides at 5.8 GHz. Fabricated using a standard 180 nm CMOS process, the amplifier achieves input and output matching of -14.7 dB and -29.7 dB, respectively. To achieve a high power level and efficiency, accurate optimization through power matching, Power Added Efficiency (PAE), and the design of the transformer are carried out while the supply voltage is limited to 1.8 V. Measurement results show a 20 dBm output power with a PAE as high as 32.5%, which makes the PA suitable for application, and it can be implanted while arrayed with various antenna arrays. Finally, a FOM is introduced to compare the performance of the work with similar works in the literature.

Design of a Current Sensing System with TIA Gain of 160 dBΩ and Input-Referred Noise of 1.8 pArms for Biosensor.

This paper proposes a high-gain low-noise current signal detection system for biosensors. When the biomaterial is attached to the biosensor, the current flowing through the bias voltage is changed so that the biomaterial can be sensed. A resistive feedback transimpedance amplifier (TIA) is used for the biosensor requiring a bias voltage. Current changes in the biosensor can be checked by plotting the current value of the biosensor in real time on the self-made graphical user interface (GUI). Even if the bias voltage changes, the input voltage of the analog to digital converter (ADC) does not change, so it is designed to plot the current of the biosensor accurately and stably. In particular, for multi-biosensors with an array structure, a method of automatically calibrating the current between biosensors by controlling the gate bias voltage of the biosensors is proposed. Input-referred noise is reduced using a high-gain TIA and chopper technique. The proposed circuit achieves 1.8 pArms input-referred noise with a gain of 160 dBΩ and is implemented in a TSMC 130 nm CMOS process. The chip area is 2.3 mm2, and the power consumption of the current sensing system is 12 mW.

A Design of Analog Front-End with DBPSK Demodulator for Magnetic Field Wireless Network Sensors.

This paper presents an on-chip fully integrated analog front-end (AFE) with a non-coherent digital binary phase-shift keying (DBPSK) demodulator suitable for short-range magnetic field wireless communication applications. The proposed non-coherent DBPSK demodulator is designed based on using comparators to digitize the received differential analog BPSK signal. The DBPSK demodulator does not need any phase-lock loop (PLL) to detect the data and recover the clock. Moreover, the proposed demodulator provides the detected data and the recovered clock simultaneously. Even though previous studies have offered the basic structure of the AFEs, this work tries to amplify and generate the required differential BPSK signal without missing data and clock throughout the AFE, while a low voltage level signal is received at the input of the AFE. A DC-offset cancellation (DCOC), a cascaded variable gain amplifier (VGA), and a single-to-differential (STOD) converter are employed to construct the implemented AFE. The simulation results indicate that the AFE provides a dynamic range of 0 dB to 40 dB power gain with 2 dB resolution. Measurement results show the minimum detectable voltage at the input of AFE is obtained at 20 mV peak-to-peak. The AFE and the proposed DBSPK demodulator are analyzed and fabricated in a 130 nm Bipolar-CMOS-DMOS (BCD) technology to recover the maximum data rate of 32 kbps where the carrier frequency is 128 kHz. The implemented DCOC, cascaded VGA, STOD, and the demodulator occupy 0.15 mm2, 0.063 mm2, 0.045 mm2, and 0.03 mm2 of area, respectively. The AFE and the demodulator consume 2.9 mA and 0.15 mA of current from an external 5 V power supply, respectively.

A High-Power 3P3T Cross Antenna Switch with Low Harmonic Distortion and Enhanced Isolation Using T-Type Pull-Down Path for Cellular Mobile Devices.

This paper presents a radio frequency (RF) triple pole triple throw 3P3T cross antenna switch for cellular mobile devices. The negative biasing scheme was applied to improve the power-handling capability and linearity of the switch by increasing the maximum tolerable voltage drop across the drain and source and reverse biasing the parasitic junction diodes. To avoid signal reflection through the antenna in off-state, all the antenna ports were equipped with 50-ohm termination to provide the pull-down path. Considering the simultaneous operation of antenna ports in different switch cases, the presented T-type pull-down path demonstrated improvement of isolation by over 15 dB. Using stacked switches, the 3P3T handled the input power level of over 35 dBm. The chip was manufactured in 65 nm complementary metal oxide semiconductor (CMOS) silicon on insulator (SOI) technology with a die size of 790 × 730 µm. The proposed structure achieved insertion loss, isolation, and voltage standing wave ratio (VSWR) of less than -0.9 dB, -40 dB, and 1.6, respectively, when the input signal was 3.8 GHz. The measured results prove the implemented switch shows the second and third harmonic distortion performances of less than -60 dBm when the input power level and frequency are 25 dBm and 3.8 GHz, respectively.

A Low-Power Analog Processor-in-Memory-Based Convolutional Neural Network for Biosensor Applications.

This paper presents an on-chip implementation of an analog processor-in-memory (PIM)-based convolutional neural network (CNN) in a biosensor. The operator was designed with low power to implement CNN as an on-chip device on the biosensor, which consists of plates of 32 × 32 material. In this paper, 10T SRAM-based analog PIM, which performs multiple and average (MAV) operations with multiplication and accumulation (MAC), is used as a filter to implement CNN at low power. PIM proceeds with MAV operations, with feature extraction as a filter, using an analog method. To prepare the input feature, an input matrix is formed by scanning a 32 × 32 biosensor based on a digital controller operating at 32 MHz frequency. Memory reuse techniques were applied to the analog SRAM filter, which is the core of low power implementation, and in order to accurately grasp the MAC operational efficiency and classification, we modeled and trained numerous input features based on biosignal data, confirming the classification. When the learned weight data was input, 19 mW of power was consumed during analog-based MAC operation. The implementation showed an energy efficiency of 5.38 TOPS/W and was differentiated through the implementation of 8 bits of high resolution in the 180 nm CMOS process.

A Configurable and Fully Synthesizable RTL-Based Convolutional Neural Network for Biosensor Applications.

This paper presents a register-transistor level (RTL) based convolutional neural network (CNN) for biosensor applications. Biosensor-based diseases detection by DNA identification using biosensors is currently needed. We proposed a synthesizable RTL-based CNN architecture for this purpose. The adopted technique of parallel computation of multiplication and accumulation (MAC) approach optimizes the hardware overhead by significantly reducing the arithmetic calculation and achieves instant results. While multiplier bank sharing throughout the convolutional operation with fully connected operation significantly reduces the implementation area. The CNN model is trained in MATLAB® on MNIST® handwritten dataset. For validation, the image pixel array from MNIST® handwritten dataset is applied on proposed RTL-based CNN architecture for biosensor applications in ModelSim®. The consistency is checked with multiple test samples and 92% accuracy is achieved. The proposed idea is implemented in 28 nm CMOS technology. It occupies 9.986 mm2 of the total area. The power requirement is 2.93 W from 1.8 V supply. The total time taken is 8.6538 ms.

A 0.617-2.7 GHz Highly Linear High-Power Dual Port 15 Throws Antenna Switch Module (DP15T-ASM) with Branched-Antenna Technique and Termination Mode.

This paper presents a Dual-Port-15-Throw (DP15T) antenna switch module (ASM) Radio Frequency (RF) switch implemented by a branched antenna technique which has a high linearity for wireless communications and various frequency bands, including a low- frequency band of 617-960 MHz, a mid-frequency band of 1.4-2.2 GHz, and a high-frequency band of 2.3-2.7 GHz. To obtain an acceptable Insertion Loss (IL) and provide a consistent input for each throw, a branched antenna technique is proposed that distributes a unified magnetic field at the inputs of the throws. The other role of the proposed antenna is to increase the inductance effects for the closer ports to the antenna pad in order to decrease IL at higher frequencies. The module is enhanced by two termination modes for each antenna path to terminate the antenna when the switch is not operating. The module is fabricated in the silicon-on-insulator CMOS process. The measurement results show a maximum IMD2 and IMD3 of -100 dBm, while for the second and third harmonics the maximum value is -89 dBc. The module operates with a maximum power handling of 35 dBm. Experimental results show a maximum IL of 0.34 and 0.92 dB and a minimum isolation of 49 dB and 35.5 dB at 0.617 GHz and 2.7 GHz frequencies, respectively. The module is implemented in a compact way to occupy an area of 0.74 mm2. The termination modes show a second harmonic of 75 dBc, which is desirable.

T/R RF Switch with 150 ns Switching Time and over 100 dBc IMD for Wideband Mobile Applications in Thick Oxide SOI Process.

This paper presents a fast-switching Transmit/Receive (T/R) Single-Pole-Double-Throw (SPDT) Radio Frequency (RF) switch. Thorough analyses have been conducted to choose the optimum number of stacks, transistor sizes, gate and body voltages, to satisfy the required specifications. This switch applies six stacks of series and shunt transistors as big as 3.9 mm/160 nm and 0.75 mm/160 nm, respectively. A negative charge pump and a voltage booster generate the negative and boosted control voltages to improve the harmonics and to keep Inter-Modulation Distortion (IMD) performance of the switch over 100 dBc. A Low Drop-Out (LDO) regulator limits the boosted voltage in Absolute Maximum Rating (AMR) conditions and improves the switch performance for Process, Voltage and Temperature (PVT) variations. To reduce the size, a dense custom-made capacitor consisting of different types of capacitors has been presented where they have been placed over each other in layout considering the Design Rule Checks (DRC) and applied in negative charge pump, voltage booster and LDO. This switch has been fabricated and tested in a 90 nm Silicon-on-Insulator (SOI) process. The second and third IMD for all specified blockers remain over 100 dBc and the switching time as fast as 150 ns has been achieved. The Insertion Loss (IL) and isolation at 2.7 GHz are -0.17 dB and -33 dB, respectively. This design consumes 145 uA from supply voltage range of 1.65 V to 1.95 V and occupies 440 × 472 µm2 of die area.

AMDB: a database of animal gut microbial communities with manually curated metadata.

Variations in gut microbiota can be explained by animal host characteristics, including host phylogeny and diet. However, there are currently no databases that allow for easy exploration of the relationship between gut microbiota and diverse animal hosts. The Animal Microbiome Database (AMDB) is the first database to provide taxonomic profiles of the gut microbiota in various animal species. AMDB contains 2530 amplicon data from 34 projects with manually curated metadata. The total data represent 467 animal species and contain 10 478 bacterial taxa. This novel database provides information regarding gut microbiota structures and the distribution of gut bacteria in animals, with an easy-to-use interface. Interactive visualizations are also available, enabling effective investigation of the relationship between the gut microbiota and animal hosts. AMDB will contribute to a better understanding of the gut microbiota of animals. AMDB is publicly available without login requirements at http://leb.snu.ac.kr/amdb.

A Low-Band Multi-Gain LNA Design for Diversity Receive Module with 1.2 dB NF.

This paper presents and discusses a Low-Band (LB) Low Noise Amplifier (LNA) design for a diversity receive module where the application is for multi-mode cellular handsets. The LB LNA covers the frequency range between 617 MHz to 960 MHz in 5 different frequency bands and a 5 Pole Single Throw (5PST) switch selects the different frequency bands where two of them are for the main and three for the auxiliary bands. The presented structure covers the gain modes from -12 to 18 dB with 6 dB gain steps where each gain mode has a different current consumption. In order to achieve the Noise Figure (NF) specifications in high gain modes, we have adopted a cascode Common-Source (CS) with inductive source degeneration structure for this design. To achieve the S11 parameters and current consumption specifications, the core and cascode transistors for high gain modes (18 dB, 12 dB, and 6 dB) and low gain modes (0 dB, -6 dB, and -12 dB) have been separated. Nevertheless, to keep the area low and keep the phase discontinuity within ±10∘, we have shared the degeneration and load inductors between two cores. To compensate the performance for Process, Voltage, and Temperature (PVT) variations, the structure applies a Low Drop-Out (LDO) regulator and a corner case voltage compensator. The design has been proceeded in a 65-nm RSB process design kit and the supply voltage is 1 V. For 18 dB and -12 dB gain modes as two examples, the NF, current consumption, and Input Third Order Intercept Point (IIP3) values are 1.2 dB and 16 dB, 10.8 mA and 1.2 mA, and -6 dBm and 8 dBm, respectively.

Emotional well-being and gut microbiome profiles by enterotype.

With increasing attention being paid to improving emotional well-being, recent evidence points to gut microbiota as a key player in regulating mental and physical health via bidirectional communication between the brain and gut. Here, we examine the association between emotional well-being and gut microbiome profiles (i.e., gut microbiome composition, diversity, and the moderating role of the enterotypes) among healthy Korean adults (n = 83, mean age = 48.9, SD = 13.2). The research was performed using high-throughput 16S rRNA gene sequencing to obtain gut microbiome profiles, as well as a self-report survey that included the Positive Affect Negative Affect Schedule (PANAS). The cluster-based analysis identified two enterotypes dominated by the genera Bacteroides (n = 49) and Prevotella (n = 34). Generalized linear regression analysis reveals significant associations between positive emotion and gut microbiome diversity (Shannon Index) among participants in the Prevotella dominant group, whereas no such relationship emerged among participants in the Bacteroides group. Moreover, a novel genus from the family Lachnospiraceae is associated with emotional well-being scores, both positive and negative. Together, the current findings highlight the enterotype-specific links between the gut microbiota community and emotion in healthy adults and suggest the possible roles of the gut microbiome in promoting mental health.