The Collapsible Light Trap: a portable Pennsylvania Light Trap for collecting aquatic insects.

A Collapsible Light Trap (CLT) for collecting insects, particularly aquatic insects, is described here. CLT is a modified Pennsylvania Light Trap with the advantage of being collapsible and lightweight to be carried in a small backpack and very easy to set up in the field. CLT is equipped with LED light strip wrapped around a PVC tube and can be connected to a regular 12 V / 7 Ah battery, running for more than 48 uninterrupted hours. Complete CLT weighs 0.8-1.0 kg, depending on the metal used, and the battery weighs around 2 kg, being easily transportable to more remote collecting areas. Over the years, CLTs have been used for collecting and describing the diversity of aquatic insects from Brazil, particularly caddisflies. Depending on the locality, only one trap for one night can collect over a thousand insect specimens and more than 200 individuals of caddisflies.

Tag SNP selection for prediction of adaptation traits in Braford and Hereford cattle using Bayesian methods.

This study utilized Bayesian inference in a genome-wide association study (GWAS) to identify genetic markers associated with traits relevant to the adaptation of Hereford and Braford cattle breeds. We focused on eye pigmentation (EP), weaning hair coat (WHC), yearling hair coat (YHC), and breeding standard (BS). Our dataset comprised 126,290 animals in the pedigree. Out of these, 233 sires were genotyped using high-density (HD) chips, and 3750 animals with medium-density (50 K) single-nucleotide polymorphism (SNP) chips. Employing the Bayes B method with a prior probability of π = 0.99, we identified and tagged single nucleotide polymorphisms (Tag SNPs), ranging from 18 to 117 SNPs depending on the trait. These Tag SNPs facilitated the construction of reduced SNP panels. We then evaluated the predictive accuracy of these panels in comparison to traditional medium-density SNP chips. The accuracy of genomic predictions using these reduced panels varied significantly depending on the clustering method, ranging from 0.13 to 0.65. Additionally, we conducted functional enrichment analysis that found genes associated with the most informative SNP markers in the current study, thereby providing biological insights into the genomic basis of these traits.

NOS2 and COX-2 Co-Expression Promotes Cancer Progression: A Potential Target for Developing Agents to Prevent or Treat Highly Aggressive Breast Cancer.

Nitric oxide (NO) and reactive nitrogen species (RNS) exert profound biological impacts dictated by their chemistry. Understanding their spatial distribution is essential for deciphering their roles in diverse biological processes. This review establishes a framework for the chemical biology of NO and RNS, exploring their dynamic reactions within the context of cancer. Concentration-dependent signaling reveals distinctive processes in cancer, with three levels of NO influencing oncogenic properties. In this context, NO plays a crucial role in cancer cell proliferation, metastasis, chemotherapy resistance, and immune suppression. Increased NOS2 expression correlates with poor survival across different tumors, including breast cancer. Additionally, NOS2 can crosstalk with the proinflammatory enzyme cyclooxygenase-2 (COX-2) to promote cancer progression. NOS2 and COX-2 co-expression establishes a positive feed-forward loop, driving immunosuppression and metastasis in estrogen receptor-negative (ER-) breast cancer. Spatial evaluation of NOS2 and COX-2 reveals orthogonal expression, suggesting the unique roles of these niches in the tumor microenvironment (TME). NOS2 and COX2 niche formation requires IFN-γ and cytokine-releasing cells. These niches contribute to poor clinical outcomes, emphasizing their role in cancer progression. Strategies to target these markers include direct inhibition, involving pan-inhibitors and selective inhibitors, as well as indirect approaches targeting their induction or downstream effectors. Compounds from cruciferous vegetables are potential candidates for NOS2 and COX-2 inhibition offering therapeutic applications. Thus, understanding the chemical biology of NO and RNS, their spatial distribution, and their implications in cancer progression provides valuable insights for developing targeted therapies and preventive strategies.

Solvent Isotherms and Structural Transitions in Nanoparticle Superlattice Assembly.

We introduce a Molecular Theory for Compressible Fluids (MOLT-CF) that enables us to compute free energies and other thermodynamic functions for nanoparticle superlattices with any solvent content, including the dry limit. Quantitative agreement is observed between MOLT-CF and united-atom molecular dynamics simulations performed to assess the reliability and precision of the theory. Among other predictions, MOLT-CF shows that the amount of solvent within the superlattice decreases approximately linearly with its vapor pressure and that in the late stages of drying, solvent-filled voids form at lattice interstitials. Applied to single-component superlattices, MOLT-CF predicts fcc-to-bcc Bain transitions for decreasing vapor pressure and for increasing ligand length, both in agreement with experimental results. We explore the stability of other single-component phases and show that the C14 Frank-Kasper phase, which has been reported in experiments, is not a global free-energy minimum. Implications for precise assembly and prediction of multicomponent nanoparticle systems are discussed.

Antibacterial, antibiofilm, and antivirulence potential of the main diterpenes from Copaifera spp. oleoresins against multidrug-resistant bacteria.

To evaluate the antibacterial, antibiofilm and antivirulence potential of the main diterpenes from Copaifera spp. oleoresins against multidrug-resistant (MDR) bacteria. Antimicrobial assays included determination of the Minimum Inhibitory Concentration (MIC), Minimum Bactericidal Concentration (MBC), Minimum Inhibitory Concentration of Biofilm (MICB50), as well as synergistic and antivirulence assays for eight diterpenes against MDR. The tests revealed that two diterpenes (named 1 and 5) showed the best results, with MIC and MBC between 12.5 and 50 µg/mL against most MDR bacteria. These diterpenes exhibited promising MICB50 in concentration between 3.12-25 µg/mL but showed no synergistic antimicrobial activity. In the assessment of antivirulence activity, diterpenes 1 and 5 inhibited only one of the virulence factors evaluated (Dnase) produced by some strains of S. aureus at subinhibitory concentration (6.25 µg/mL). Results obtained indicated that diterpenes isolated from Copaifera oleoresin plays an important part in the search of new antibacterial and antibiofilm agents that can act against MDR bacteria.

Development of a new assay for quantification of parasite load of intracellular Leishmania sp. in macrophages using flow cytometry.

Finding novel methodologies that enhance the precision, agility, and standardization of drug discovery is crucial for studying leishmaniasis. The slide count is the technique most used to assess the leishmanicidal effect of a given drug in vitro. Despite being consolidated in the scientific environment, it presents several difficulties in its execution, assessment, and results. In addition to being laborious, this technique takes time, both for the preparation of the material for analysis and for the counting itself. Our research group suggests a fresh approach to address this requirement, which involves utilizing nuclear labeling with propidium iodide and flow cytometry to determine the quantity of Leishmania sp. parasites present in macrophages in vitro. Our results show that the fluorescence of infected samples increases as the infection rate increases. Using Pearson's Correlation analysis, it was possible to establish a correlation coefficient (Pearson r = 0.9473) that was strongly positive, linear, and directly proportional to the fluorescence and infection rate variables. Thus, it is possible to infer a mathematical equation through linear regression to estimate the number of parasites in each sample using the Relative Fluorescence Units (RFU) values. This new methodology opens space for the possibility of using this methodological resource in the in vitro quantification of Leishmania in macrophages.

Efficacy and safety of the oral Janus kinase 1 inhibitor povorcitinib (INCB054707) in patients with hidradenitis suppurativa in a phase 2, randomized, double-blind, dose-ranging, placebo-controlled study.

BACKGROUND: Janus kinase 1 inhibition may alleviate hidradenitis suppurativa (HS)-associated inflammation and improve symptoms. OBJECTIVE: To assess efficacy and safety of povorcitinib (selective oral Janus kinase 1 inhibitor) in HS. METHODS: This placebo-controlled phase 2 study randomized patients with HS 1:1:1:1 to receive povorcitinib 15, 45, or 75 mg or placebo for 16 weeks. Primary and key secondary end points were mean change from baseline in abscess and inflammatory nodule count and percentage of patients achieving HS Clinical Response at week 16. RESULTS: Of 209 patients randomized (15 mg, n = 52; 45 mg, n = 52; 75 mg, n = 53; placebo, n = 52), 83.3% completed the 16-week treatment. At week 16, povorcitinib significantly reduced abscess and inflammatory nodule count from baseline (least squares mean [SE] change: 15 mg, -5.2 [0.9], P = .0277; 45 mg, -6.9 [0.9], P = .0006; 75 mg, -6.3 [0.9], P = .0021) versus placebo (-2.5 [0.9]). More povorcitinib-treated patients achieved HS Clinical Response at week 16 (15 mg, 48.1%, P = .0445; 45 mg, 44.2%, P = .0998; 75 mg, 45.3%, P = .0829) versus placebo (28.8%). A total of 60.0% and 65.4% of povorcitinib- and placebo-treated patients had adverse events. LIMITATIONS: Baseline lesion counts were mildly imbalanced between groups. CONCLUSION: Povorcitinib demonstrated efficacy in HS, with no evidence of increased incidence of adverse events among doses.

Transmission dynamics of SARS-CoV-2 variants in the Brazilian state of Pará.

Introduction: After three years since the beginning of the pandemic, the new coronavirus continues to raise several questions regarding its infectious process and host response. Several mutations occurred in different regions of the SARS-CoV-2 genome, such as in the spike gene, causing the emergence of variants of concern and interest (VOCs and VOIs), of which some present higher transmissibility and virulence, especially among patients with previous comorbidities. It is essential to understand its spread dynamics to prevent and control new biological threats that may occur in the future. In this population_based retrospective observational study, we generated data and used public databases to understand SARS-CoV-2 dynamics. Methods: We sequenced 1,003 SARS-CoV-2 genomes from naso-oropharyngeal swabs and saliva samples from Pará from May 2020 to October 2022. To gather epidemiological data from Brazil and the world, we used FIOCRUZ and GISAID databases. Results: Regarding our samples, 496 (49.45%) were derived from female participants and 507 (50.55%) from male participants, and the average age was 43 years old. The Gamma variant presented the highest number of cases, with 290 (28.91%) cases, followed by delta with 53 (5.28%). Moreover, we found seven (0.69%) Omicron cases and 651 (64.9%) non-VOC cases. A significant association was observed between sex and the clinical condition (female, p = 8.65e-08; male, p = 0.008961) and age (p = 3.6e-10). Discussion: Although gamma had been officially identified only in December 2020/January 2021, we identified a gamma case from Belém (capital of Pará State) dated May 2020 and three other cases in October 2020. This indicates that this variant was circulating in the North region of Brazil several months before its formal identification and that Gamma demonstrated its actual transmission capacity only at the end of 2020. Furthermore, the public data analysis showed that SARS-CoV-2 dispersion dynamics differed in Brazil as Gamma played an important role here, while most other countries reported a new infection caused by the Delta variant. The genetic and epidemiological information of this study reinforces the relevance of having a robust genomic surveillance service that allows better management of the pandemic and that provides efficient solutions to possible new disease-causing agents.

Global mangrove soil organic carbon stocks dataset at 30 m resolution for the year 2020 based on spatiotemporal predictive machine learning.

This dataset presents global soil organic carbon stocks in mangrove forests at 30 m resolution, predicted for 2020. We used spatiotemporal ensemble machine learning to produce predictions of soil organic carbon content and bulk density (BD) to 1 m soil depth, which were then aggregated to calculate soil organic carbon stocks. This was done by using training data points of both SOC (%) and BD in mangroves from a global dataset and from recently published studies, and globally consistent predictive covariate layers. A total of 10,331 soil samples were validated to have SOC (%) measurements and were used for predictive soil mapping. We used time-series remote sensing data specific to time periods when the training data were sampled, as well as long-term (static) layers to train an ensemble of machine learning model. Ensemble models were used to improve performance, robustness and unbiasedness as opposed to just using one learner. In addition, we performed spatial cross-validation by using spatial blocking of training data points to assess model performance. We predicted SOC stocks for the 2020 time period and applied them to a 2020 mangrove extent map, presenting both mean predictions and prediction intervals to represent the uncertainty around our predictions. Predictions are available for download under CC-BY license from 10.5281/zenodo.7729491 and also as Cloud-Optimized GeoTIFFs (global mosaics).

Effect of antibiotics and low-crude protein diets on growth performance, health, immune response, and fecal microbiota of growing pigs.

This study aimed to investigate the effects of diets with and without antibiotics supplementation and diets with 18.5% and 13.0% crude protein (CP) on growth performance, carcass characteristics, disease incidence, fecal microbiota, immune response, and antioxidant capacity of growing pigs. One hundred and eighty pigs (59-day-old; 18.5 ±â€…2.5 kg) were distributed in a randomized complete block design in a 2 × 2 factorial arrangement, nine replicates, and five pigs per pen. The factors were CP (18.5% or 13.0%) and antibiotics (none or 100 mg/kg tiamulin + 506 mg/kg oxytetracycline). Medicated diets were fed from days 59 to 73. After that, all pigs were fed their respective CP diets from 73 to 87 days. Data were analyzed using the Mixed procedure in SAS version 9.4. From days 59 to 73, pigs fed antibiotics diets had higher (P < 0.05) average daily feed intake (ADFI), average daily weight gain (ADG), gain to feed ratio (G:F), compared to the diets without antibiotics. From days 73 to 87 (postmedicated period), any previous supplementation of antibiotics did not affect pig growth performance. Overall (days 59 to 87), pigs-fed antibiotics diets had higher (P < 0.05) G:F compared to pigs-fed diets without antibiotics. In all periods evaluated, pigs fed 18.5% CP diets had higher (P < 0.05) ADG and G:F compared to pigs fed 13.0% CP. Pigs fed the 13.0% CP diets had lower (P < 0.05) fecal score and diarrhea incidence than those fed 18.5% CP. Pigs fed 18.5% CP diets had improved (P < 0.05) loin area compared to pigs-fed diets with 13.0% CP. At 66 days of age, pigs-fed antibiotics diets had lower (P < 0.05) alpha diversity estimated with Shannon and Simpson compared to the pig-fed diets without antibiotics. At family level, pigs fed 18.5% CP diets had higher (P < 0.05) relative abundance of Streptococcaceae, and lower (P < 0.05) relative abundance of Clostridiaceae at days 66 and 87 compared with pigs fed 13.0% CP. Pigs-fed antibiotics diets had lower (P < 0.05) immunoglobulin G and protein carbonyl concentrations at day 66 compared to the pigs-fed diets without antibiotics. The reduction of dietary CP from 18.5% to 13.0% reduced the growth performance and loin muscle area of growing pigs, although it was effective to reduce diarrhea incidence. Antibiotics improved growth performance, lowered diarrhea incidence, improved components of the humoral immune response, and reduced microbiota diversity. However, in the postmedicated period, we found no residual effect on the general health of the animals, and considering the overall period, only G:F was improved by the use of antibiotics.

Dietary antibiotics have been used in pig farming practices to avoid health problems and improve animal growth performance. However, their use in production animals is considered a global health challenge, due to its association with selection of resistance in zoonotic bacteria. Another negative impact of pig farming that has gained attention is related to environmental pollution due to the excretion of nitrogenous compounds. Reducing dietary crude protein content has become a goal in the pig feed industry due to the limited availability and high cost of dietary protein sources, as well as the aim of enhancing gut health in pigs. Thus, the aim of this study was to investigate the effects of diets with and without antibiotics supplementation and diets with 18.5% and 13.0% crude protein for pigs. The reduction of dietary crude protein in this study reduced growth performance, although it was effective to reduce diarrhea incidence. Antibiotics improved growth performance, positively affected the overall health of animals, and reduced microbiota diversity. However, during the postmedicated period, we found no residual effect on the general health of the animals, and considering the overall period, only gain to feed ratio was improved by the use of antibiotics.

MILimbEEG: A dataset of EEG signals related to upper and lower limb execution of motor and motor imagery tasks.

Biomedical Electroencephalography (EEG) signals are the result of measuring the electric potential difference generated on the scalp surface by neural activity corresponding to each brain area. Accurate and automatic detection of neural activity from the upper and lower limbs using EEG may be helpful in rehabilitating people suffering from mobility limitations or disabilities. This article presents a dataset containing 7440 CSV files from 60 test subjects during motor and motor imagery tasks. The motor and motor imagery tasks performed by the test subjects were: Closing Left Hand (CLH), Closing Right Hand (CRH), Dorsal flexion of Left Foot (DLF), Plantar flexion of Left Foot (PLF), Dorsal flexion of Right Foot (DRF), Plantar flexion of Right Foot (PRF) and Resting in between tasks (Rest). The volunteers were recruited from research colleagues at ESPOL and patients at the Luis Vernaza Hospital in Guayaquil, Ecuador. Each CSV file has 501 rows, of which the first one lists the electrodes from 0 to 15, and the remaining 500 rows correspond to 500 data recorded during the task is performed due to sample rate. In addition, each file has 17 columns, of which the first one indicates the sampling number and the remaining 16 columns represent 16 surface EEG electrodes. As a data recording equipment, the OpenBCI is used in a monopolar setup with a sampling rate of 125 Hz. This work includes statistical measures about the demographic information of all recruited test subjects. Finally, we outline the experimental methodology used to record EEG signals during upper and lower limb task execution. This dataset is called MILimbEEG and contains microvolt (µV) EEG signals acquired during motor and motor imagery tasks. The collected data may facilitate the evaluation of EEG signal detection and classification models dedicated to task recognition.

Theoretical treatment of complex coacervate core micelles: structure and pH-induced disassembly.

Complex coacervate core micelles (C3Ms) are supramolecular soft nanostructures formed by the assembly of a block copolymer and an oppositely charged homopolymer. The coacervation of the charged segments in both macromolecules drives the formation of the core of the C3M, while the neutral block of the copolymer forms the corona. This work introduces a molecular theory (MOLT) that predicts the internal structure and stimuli-responsive properties of C3Ms and explicitly considers the chemical architecture of the polyelectrolytes, their acid-based equilibria and electrostatic and non-electrostatic interactions. In order to accurately predict complex coacervation, the correlations between charged species are incorporated into MOLT as ion-pairing processes, which are modeled using a coupled chemical equilibrium formalism. Very good agreement was observed between the experimental results in the literature and MOLT predictions for the scaling relationships that relate the dimensions of the micelle (aggregation number and sizes of the micelle and the core) to the lengths of the different blocks. MOLT was used to study the disassembly of the micelles when the solution pH is driven away from the value that guarantees the charge stoichiometry of the core. This study reveals that very sharp disassembly transitions can be obtained by tuning the length or architecture of the copolymer component, thereby suggesting potential routes to design C3Ms capable of releasing their components at very precise pH values.

Adaptive PI Controller Based on a Reinforcement Learning Algorithm for Speed Control of a DC Motor.

Automated industrial processes require a controller to obtain an output signal similar to the reference indicated by the user. There are controllers such as PIDs, which are efficient if the system does not change its initial conditions. However, if this is not the case, the controller must be retuned, affecting production times. In this work, an adaptive PID controller is developed for a DC motor speed plant using an artificial intelligence algorithm based on reinforcement learning. This algorithm uses an actor-critic agent, where its objective is to optimize the actor's policy and train a critic for rewards. This will generate the appropriate gains without the need to know the system. The Deep Deterministic Policy Gradient with Twin Delayed (DDPG TD3) was used, with a network composed of 300 neurons for the agent's learning. Finally, the performance of the obtained controller is compared with a classical control one using a cost function.

OPTICAL COHERENCE TOMOGRAPHY ANGIOGRAPHY BIOMARKERS AND MICROPERIMETRY FEATURES IN BEHÇET'S UVEITIS.

PURPOSE: To evaluate the parafoveal macular microvasculature and the macular function in patients with retinal vasculitis associated with Behçet's uveitis. METHODS: In 14 patients with inactive Behçet's uveitis and 26 control individuals (13 with nonocular Behçet's syndrome and 13 healthy subjects), we analyzed the retinal nerve fiber layer, ganglion cell layer, full retinal thickness, foveal avascular zone area and sectorial parafoveal vascular density in the superficial vascular plexus, intermediate capillary plexus, and deep capillary plexus using SPECTRALIS optical coherence tomography (OCT) 2 and OCT angiography. Macular sensitivity was analyzed using an MP-3 microperimeter. RESULTS: Eighteen eyes (78%) had a best-corrected visual acuity ≥ 20/25. Significant differences were found in Behçet's uveitis in comparison with the controls on the OCT and OCT angiography: 14.8%, 22.4%, and 14.9% ganglion cell layer thinning in the global, nasal, and inferior sectors, respectively; 6%, 13.2%, and 7.5% full retinal thickness thinning in the superior, nasal, and inferior sectors; and 16.8%, 14.9%, 23.6%, 15.8%, and 12.6% mean deep capillary plexus density reduction in the global, superior, nasal, inferior, and temporal sectors. Microperimetry data demonstrated significant mean reductions of 21% and 23.6% in central and average macular sensitivities and 28.8%, 40.4%, 27.7%, and 24.2% in the superior, nasal, inferior, and temporal sectors, respectively. Outer plexiform layer elevations were observed in Behçet's uveitis (69.6%). CONCLUSION: Behçet's uveitis presented structural and functional macular damage despite good best-corrected visual acuity, mainly affecting the nasal sector and the deep capillary plexus. On OCT and OCT angiography, quantitative and qualitative changes can be valuable biomarkers of ocular involvement in Behçet's syndrome.

Individualized risk assessment of distant metastases in oral cavity carcinoma: a validated predictive-score model.

BACKGROUND: We aimed to develop and validate a risk-scoring system for distant metastases (DMs) in oral cavity carcinoma (OCC). METHODS: Patients with OCC who were treated at 4 tertiary cancer institutions with curative surgery with or without postoperative radiation/chemoradiation therapy were randomly assigned to discovery or validation cohorts (3:2 ratio). Cases were staged on the basis of tumor, node, and metastasis staging according to the eighth edition of the American Joint Committee on Cancer/Union for International Cancer Control guidelines. Predictors of DMs on multivariable analysis in the discovery cohort were used to develop a risk-score model and classify patients into risk groups. The utility of the risk classification was evaluated in the validation cohort. RESULTS: Overall, 2749 patients were analyzed. Predictors (risk score coefficient) of DMs in the discovery cohort were the following: pathological stage (p)T3-4 (0.4), pN+ (N1: 0.8; N2: 1.0; N3: 1.5), histologic grade (G) 3 (G3, 0.7), and lymphovascular invasion (0.4). The DM risk groups were defined by the sum of the following risk score coefficients: high (>1.7), intermediate (0.7-1.7), and standard risk (<0.7). The 5-year DM rates (high/intermediate/standard risk groups) were 30%/15%/4% in the discovery cohort (C-index = 0.79) and 35%/16%/5% in the validation cohort, respectively (C-index = 0.77; both P < .001). In the whole cohort, this predictive model showed excellent discriminative ability in predicting DMs without locoregional failure (29%/11%/1%), later (>2 year) DMs (11%/4%/2%), and DMs in patients treated with surgery (20%/12%/5%), postoperative radiation therapy (34%/17%/4%), and postoperative chemoradiation therapy (39%/18%/7%) (all P < .001). The 5-year overall survival rates in the overall cohort were 25%/51%/67% (P < .001). CONCLUSIONS: Patients at higher risk for DMs were identified by use of a predictive-score model for DMs that included pT3-4, pN1/2/3, G3, and lymphovascular invasion. Identified patients may be evaluated for individualized risk-adaptive treatment escalation and/or surveillance strategies.

A 3D Printed, Bionic Hand Powered by EMG Signals and Controlled by an Online Neural Network.

About 8% of the Ecuadorian population suffers some type of amputation of upper or lower limbs. Due to the high cost of a prosthesis and the fact that the salary of an average worker in the country reached 248 USD in August 2021, they experience a great labor disadvantage and only 17% of them are employed. Thanks to advances in 3D printing and the accessibility of bioelectric sensors, it is now possible to create economically accessible proposals. This work proposes the design of a hand prosthesis that uses electromyography (EMG) signals and neural networks for real-time control. The integrated system has a mechanical and electronic design, and the latter integrates artificial intelligence for control. To train the algorithm, an experimental methodology was developed to record muscle activity in upper extremities associated with specific tasks, using three EMG surface sensors. These data were used to train a five-layer neural network. the trained model was compressed and exported using TensorflowLite. The prosthesis consisted of a gripper and a pivot base, which were designed in Fusion 360 considering the movement restrictions and the maximum loads. It was actuated in real time thanks to the design of an electronic circuit that used an ESP32 development board, which was responsible for recording, processing and classifying the EMG signals associated with a motor intention, and to actuate the hand prosthesis. As a result of this work, a database with 60 electromyographic activity records from three tasks was released. The classification algorithm was able to detect the three muscle tasks with an accuracy of 78.67% and a response time of 80 ms. Finally, the 3D printed prosthesis was able to support a weight of 500 g with a safety factor equal to 15.

Evolving Memristive Reservoir.

In light of the dynamic plasticity, nanosize, and energy efficiency of memristors, memristive reservoirs have attracted increasing attention in diverse fields of research recently. However, limited by deterministic hardware implementation, hardware reservoir adaptation is hard to realize. Existing evolutionary algorithms for evolving reservoirs are not designed for hardware implementation. They often ignore the circuit scalability and feasibility of the memristive reservoirs. In this work, based on the reconfigurable memristive units (RMUs), we first propose an evolvable memristive reservoir circuit that is capable of adaptive evolution for varying tasks, where the configuration signals of memristor are evolved directly avoiding the device variance of the memristors. Second, considering the feasibility and scalability of memristive circuits, we propose a scalable algorithm for evolving the proposed reconfigurable memristive reservoir circuit, where the reservoir circuit will not only be valid according to the circuit laws but also has the sparse topology, alleviating the scalability issue and ensuring the circuit feasibility during the evolution. Finally, we apply our proposed scalable algorithm to evolve the reconfigurable memristive reservoir circuits for a wave generation task, six prediction tasks, and one classification task. Through experiments, the feasibility and superiority of our proposed evolvable memristive reservoir circuit are demonstrated.

Modulation of Disease-Associated Pathways in Hidradenitis Suppurativa by the Janus Kinase 1 Inhibitor Povorcitinib: Transcriptomic and Proteomic Analyses of Two Phase 2 Studies.

Janus kinase (JAK)/signal transducer and activator of transcription signaling (STAT) has been implicated in the pathophysiology of hidradenitis suppurativa (HS). This study evaluated treatment-related transcriptomic and proteomic changes in patients with moderate-to-severe HS treated with the investigational oral JAK1-selective inhibitor povorcitinib (INCB054707) in two phase 2 trials. Lesional skin punch biopsies (baseline and Week 8) were taken from active HS lesions of patients receiving povorcitinib (15 or 30 mg) once daily (QD) or a placebo. RNA-seq and gene set enrichment analyses were used to evaluate the effects of povorcitinib on differential gene expression among previously reported gene signatures from HS and wounded skin. The number of differentially expressed genes was the greatest in the 30 mg povorcitinib QD dose group, consistent with the published efficacy results. Notably, the genes impacted reflected JAK/STAT signaling transcripts downstream of TNF-α signaling, or those regulated by TGF-ß. Proteomic analyses were conducted on blood samples obtained at baseline and Weeks 4 and 8 from patients receiving povorcitinib (15, 30, 60, or 90 mg) QD or placebo. Povorcitinib was associated with transcriptomic downregulation of multiple HS and inflammatory signaling markers as well as the reversal of gene expression previously associated with HS lesional and wounded skin. Povorcitinib also demonstrated dose-dependent modulation of several proteins implicated in HS pathophysiology, with changes observed by Week 4. The reversal of HS lesional gene signatures and rapid, dose-dependent protein regulation highlight the potential of JAK1 inhibition to modulate underlying disease pathology in HS.