Alterations in cell arrangements of group B streptococcus due to virulence factor expression can bias estimates of bacterial populations based on colony count measures.

Group B streptococcus (GBS) is a chain-forming commensal bacterium and opportunistic pathogen that resides in the gastrointestinal and genitourinary tract of healthy adults. GBS can cause various infections and related complications in pregnant and nonpregnant women, adults, and newborns. Investigations of the mechanisms by which GBS causes disease pathogenesis often utilize colony count assays to estimate bacterial population size in experimental models. In other streptococci, such as group A streptococcus and pneumococcus, variation in the chain length of the bacteria that can occur naturally or due to mutation can affect facets of pathogenesis, such as adherence to or colonization of a host. No studies have reported a relationship between GBS chain length and pathogenicity. Here, we used GBS strain 874391 and several derivative strains displaying longer chain-forming phenotypes (874391pgapC, 874391ΔcovR, 874391Δstp1) to assess the impact of chain length on bacterial population estimates based on the colony-forming unit (c.f.u.) assay. Disruption of GBS chains via bead beating or sonication in conjunction with fluorescence microscopy was used to compare chaining phenotypes pre- and post-disruption to detect long- and short-chain forms, respectively. We used a murine model of GBS colonization of the female reproductive tract to assess whether chaining may affect bacterial colonization dynamics in the host during chronic infection in vivo. Overall, we found that GBS exhibiting long-chain form can significantly affect population size estimates based on the colony count assay. Additionally, we found that the length of chaining of GBS can affect virulence in the reproductive tract colonization model. Collectively, these findings have implications for studies of GBS that utilize colony count assays to measure GBS populations and establish that chain length can affect infection dynamics and disease pathogenesis for this important opportunistic pathogen.

An opportunistic pathogen under stress: how Group B Streptococcus responds to cytotoxic reactive species and conditions of metal ion imbalance to survive.

Group B Streptococcus (GBS; also known as Streptococcus agalactiae) is an opportunistic bacterial pathogen that causes sepsis, meningitis, pneumonia, and skin and soft tissue infections in neonates and healthy or immunocompromised adults. GBS is well-adapted to survive in humans due to a plethora of virulence mechanisms that afford responses to support bacterial survival in dynamic host environments. These mechanisms and responses include counteraction of cell death from exposure to excess metal ions that can cause mismetallation and cytotoxicity, and strategies to combat molecules such as reactive oxygen and nitrogen species that are generated as part of innate host defence. Cytotoxicity from reactive molecules can stem from damage to proteins, DNA, and membrane lipids, potentially leading to bacterial cell death inside phagocytic cells or within extracellular spaces within the host. Deciphering the ways in which GBS responds to the stress of cytotoxic reactive molecules within the host will benefit the development of novel therapeutic and preventative strategies to manage the burden of GBS disease. This review summarizes knowledge of GBS carriage in humans and the mechanisms used by the bacteria to circumvent killing by these important elements of host immune defence: oxidative stress, nitrosative stress, and stress from metal ion intoxication/mismetallation.

Development of Quick Response (QR) Training of Tractor Component Identification, Function, Maintenance, and Safety.

Given the high variability of secondary agricultural teacher background and facility constraints, the instruction of tractor (and similar agricultural machinery) component identification, function, maintenance, and corresponding safety precautions oftentimes prove difficult and/or inconsistent. This study focused on the development and plausible application of quick response codes, commonly referred to as QR codes, placed on a demonstration tractor or machine to be used as a self-guided student learning experience for training the next generation of safe operators. This review documents a novel self-guided instruction methodology utilizing "gamification" learning theory. Content materials were derived from the nationally disseminated, open source, Gearing Up for Safety Production Agriculture Safety Training for Youth curriculum. Specifically, QR code learning modules were recommended to supplement Gearing Up for Safety, Lesson 16: Hands-On Tractor Operation of the youth worker certification component of the Pre-Operational Skills Exam.

The integration of GPS and visual navigation for autonomous navigation of an Ackerman steering mobile robot in cotton fields.

Autonomous navigation in agricultural fields presents a unique challenge due to the unpredictable outdoor environment. Various approaches have been explored to tackle this task, each with its own set of challenges. These include GPS guidance, which faces availability issues and struggles to avoid obstacles, and vision guidance techniques, which are sensitive to changes in light, weeds, and crop growth. This study proposes a novel idea that combining GPS and visual navigation offers an optimal solution for autonomous navigation in agricultural fields. Three solutions for autonomous navigation in cotton fields were developed and evaluated. The first solution utilized a path tracking algorithm, Pure Pursuit, to follow GPS coordinates and guide a mobile robot. It achieved an average lateral deviation of 8.3 cm from the pre-recorded path. The second solution employed a deep learning model, specifically a fully convolutional neural network for semantic segmentation, to detect paths between cotton rows. The mobile rover then navigated using the Dynamic Window Approach (DWA) path planning algorithm, achieving an average lateral deviation of 4.8 cm from the desired path. Finally, the two solutions were integrated for a more practical approach. GPS served as a global planner to map the field, while the deep learning model and DWA acted as a local planner for navigation and real-time decision-making. This integrated solution enabled the robot to navigate between cotton rows with an average lateral distance error of 9.5 cm, offering a more practical method for autonomous navigation in cotton fields.

Prophylactic defunctioning stomas improve clinical outcomes of anastomotic leak following rectal cancer resections: An analysis of the US Rectal Cancer Consortium.

PURPOSE: Anastomotic leak (AL) is a complication of low anterior resection (LAR) that results in substantial morbidity. There is immense interest in evaluating immediate postoperative and long-term oncologic outcomes in patients who undergo diverting loop ileostomies (DLI). The purpose of this study is to understand the relationship between fecal diversion, AL, and oncologic outcomes. METHODS: This is a retrospective multicenter cohort study using patient data obtained from the US Rectal Cancer Consortium database compiled from six academic institutions. The study population included patients with rectal adenocarcinoma undergoing LAR. The primary outcome was the incidence of AL among patients who did or did not receive DLI during LAR. Secondary outcomes included risk factors for AL, receipt of adjuvant therapy, 3-year overall survival, and 3-year recurrence. RESULTS: Of 815 patients, 38 (4.7%) suffered AL after LAR. Patients with AL were more likely to be male, have unintentional preoperative weight loss, and are less likely to undergo DLI. On multivariable analysis, DLI remained protective against AL (p < 0.001). Diverted patients were less likely to undergo future surgical procedures including additional ostomy creation, completion proctectomy, or pelvic washout for AL. Subgroup analysis of 456 patients with locally advanced disease showed that DLI was correlated with increased receipt of adjuvant therapy for patients with and without AL on univariate analysis (SHR:1.59; [95% CI 1.19-2.14]; p = 0.002), but significance was not met in multivariate models. CONCLUSION: Lack of DLI and preoperative weight loss was associated with anastomotic leak. Fecal diversion may improve the timely initiation of adjuvant oncologic therapy. The long-term outcomes following routine diverting stomas warrant further study.

Quantifying cerebral microbleeds using quantitative susceptibility mapping from magnetization-prepared rapid gradient-echo.

T1-weighted magnetization-prepared rapid gradient-echo (MPRAGE) is commonly included in brain studies for structural imaging using magnitude images; however, its phase images can provide an opportunity to assess microbleed burden using quantitative susceptibility mapping (QSM). This potential application for MPRAGE-based QSM was evaluated using in vivo and simulated measurements. Possible factors affecting image quality were also explored. Detection sensitivity was evaluated against standard multiecho gradient echo (MEGE) QSM using 3-T in vivo data of 15 subjects with a combined total of 108 confirmed microbleeds. The two methods were compared based on the microbleed size and susceptibility measurements. In addition, simulations explored the detection sensitivity of MPRAGE-QSM at different representative magnetic field strengths and echo times using microbleeds of different size, susceptibility, and location. Results showed that in vivo microbleeds appeared to be smaller (× 0.54) and of higher mean susceptibility (× 1.9) on MPRAGE-QSM than on MEGE-QSM, but total susceptibility estimates were in closer agreement (slope: 0.97, r2 : 0.94), and detection sensitivity was comparable. In simulations, QSM at 1.5 T had a low contrast-to-noise ratio that obscured the detection of many microbleeds. Signal-to-noise ratio (SNR) levels at 3 T and above resulted in better contrast and increased detection. The detection rates for microbleeds of minimum one-voxel diameter and 0.4-ppm susceptibility were 0.55, 0.80, and 0.88 at SNR levels of 1.5, 3, and 7 T, respectively. Size and total susceptibility estimates were more consistent than mean susceptibility estimates, which showed size-dependent underestimation. MPRAGE-QSM provides an opportunity to detect and quantify the size and susceptibility of microbleeds of at least one-voxel diameter at B0  of 3 T or higher with no additional time cost, when standard T2 *-weighted images are not available or have inadequate spatial resolution. The total susceptibility measure is more robust against sequence variations and might allow combining data from different protocols.

A convergent evolutionary pathway attenuating cellulose production drives enhanced virulence of some bacteria.

Bacteria adapt to selective pressure in their immediate environment in multiple ways. One mechanism involves the acquisition of independent mutations that disable or modify a key pathway, providing a signature of adaptation via convergent evolution. Extra-intestinal pathogenic Escherichia coli (ExPEC) belonging to sequence type 95 (ST95) represent a global clone frequently associated with severe human infections including acute pyelonephritis, sepsis, and neonatal meningitis. Here, we analysed a publicly available dataset of 613 ST95 genomes and identified a series of loss-of-function mutations that disrupt cellulose production or its modification in 55.3% of strains. We show the inability to produce cellulose significantly enhances ST95 invasive infection in a rat model of neonatal meningitis, leading to the disruption of intestinal barrier integrity in newborn pups and enhanced dissemination to the liver, spleen and brain. Consistent with these observations, disruption of cellulose production in ST95 augmented innate immune signalling and tissue neutrophil infiltration in a mouse model of urinary tract infection. Mutations that disrupt cellulose production were also identified in other virulent ExPEC STs, Shigella and Salmonella, suggesting a correlative association with many Enterobacteriaceae that cause severe human infection. Together, our findings provide an explanation for the emergence of hypervirulent Enterobacteriaceae clones.

Resisting death by metal: metabolism and Cu/Zn homeostasis in bacteria.

Metal ions such as zinc and copper play important roles in host-microbe interactions and their availability can drastically affect the survival of pathogenic bacteria in a host niche. Mechanisms of metal homeostasis protect bacteria from starvation, or intoxication, defined as when metals are limiting, or in excess, respectively. In this mini-review, we summarise current knowledge on the mechanisms of resistance to metal stress in bacteria, focussing specifically on the homeostasis of cellular copper and zinc. This includes a summary of the factors that subvert metal stress in bacteria, which are independent of metal efflux systems, and commentary on the role of small molecules and metabolic systems as important mediators of metal resistance.

Development of a Low-Cost Distributed Computing Pipeline for High-Throughput Cotton Phenotyping.

In this paper, we present the development of a low-cost distributed computing pipeline for cotton plant phenotyping using Raspberry Pi, Hadoop, and deep learning. Specifically, we use a cluster of several Raspberry Pis in a primary-replica distributed architecture using the Apache Hadoop ecosystem and a pre-trained Tiny-YOLOv4 model for cotton bloom detection from our past work. We feed cotton image data collected from a research field in Tifton, GA, into our cluster's distributed file system for robust file access and distributed, parallel processing. We then submit job requests to our cluster from our client to process cotton image data in a distributed and parallel fashion, from pre-processing to bloom detection and spatio-temporal map creation. Additionally, we present a comparison of our four-node cluster performance with centralized, one-, two-, and three-node clusters. This work is the first to develop a distributed computing pipeline for high-throughput cotton phenotyping in field-based agriculture.

Association of omental pedicled flap with anastomotic leak following low anterior resection for rectal cancer.

BACKGROUND AND OBJECTIVES: Anastomotic leak following colorectal anastomosis adversely impacts short-term, oncologic, and quality-of-life outcomes. This study aimed to assess the impact of omental pedicled flap (OPF) on anastomotic leak among patients undergoing low anastomotic resection (LAR) for rectal cancer using a multi-institutional database. METHODS: Adult rectal cancer patients in the US Rectal Cancer Consortium, who underwent a LAR for stage I-III rectal cancer with or without an OPF were included. Patients with missing data for surgery type and OPF use were excluded from the analysis. The primary outcome was the development of anastomotic leaks. Multivariable logistic regression was used to determine the association. RESULTS: A total of 853 patients met the inclusion criteria and OPF was used in 106 (12.4%) patients. There was no difference in age, sex, or tumor stage of patients who underwent OPF versus those who did not. OPF use was not associated with an anastomotic leak (p = 0.82), or operative blood loss (p = 0.54) but was associated with an increase in the operative duration [ß = 21.42 (95% confidence interval = 1.16, 41.67) p = 0.04]. CONCLUSIONS: Among patients undergoing LAR for rectal cancer, OPF use was associated with an increase in operative duration without any impact on the rate of anastomotic leak.

Evaluation of Inference Performance of Deep Learning Models for Real-Time Weed Detection in an Embedded Computer.

The knowledge that precision weed control in agricultural fields can reduce waste and increase productivity has led to research into autonomous machines capable of detecting and removing weeds in real time. One of the driving factors for weed detection is to develop alternatives to herbicides, which are becoming less effective as weed species develop resistance. Advances in deep learning technology have significantly improved the robustness of weed detection tasks. However, deep learning algorithms often require extensive computational resources, typically found in powerful computers that are not suitable for deployment in robotic platforms. Most ground rovers and UAVs utilize embedded computers that are portable but limited in performance. This necessitates research into deep learning models that are computationally lightweight enough to function in embedded computers for real-time applications while still maintaining a base level of detection accuracy. This paper evaluates the weed detection performance of three real-time-capable deep learning models, YOLOv4, EfficientDet, and CenterNet, when run on a deep-learning-enabled embedded computer, an Nvidia Jetson Xavier AGX. We tested the accuracy of the models in detecting 13 different species of weeds and assesses their real-time viability through their inference speeds on an embedded computer compared to a powerful deep learning PC. The results showed that YOLOv4 performed better than the other models, achieving an average inference speed of 80 ms per image and 14 frames per second on a video when run on an imbedded computer, while maintaining a mean average precision of 93.4% at a 50% IoU threshold. Furthermore, recognizing that some real-world applications may require even greater speed, and that the detection program would not be the only task running on the embedded computer, a lightweight version of the YOLOv4 model, YOLOv4-tiny, was tested for improved performance in an embedded computer. YOLOv4-tiny impressively achieved an average inference speed of 24.5 ms per image and 52 frames per second, albeit with a slightly reduced mean average precision of 89% at a 50% IoU threshold, making it an ideal choice for real-time weed detection.

The whole day matters after stroke: Study protocol for a randomized controlled trial investigating the effect of a 'sit less, move more, sleep better' program early after stroke.

BACKGROUND: Movement-related behaviours, including prolonged sedentary behaviour, physical inactivity, and poor sleep, are associated with worse functional outcomes poststroke. Addressing these co-dependent behaviours early after stroke may help to optimize recovery and improve overall quality of life for individuals with stroke. OBJECTIVE: This study aims to determine the feasibility and effect of a 'sit less, move more, sleep better' program early after stroke on functional mobility and global disability outcomes, while also exploring imaging and behavioural markers that may influence walking recovery. METHODS: The study is an assessor-blinded, single-center, parallel-group, randomized controlled trial to be completed within 24 months from July 12, 2023 to June 30, 2025. We will enroll 50 patients with acute ischemic stroke within 7 days from symptom onset, aged 18 years or older, and with ongoing walking goals. Demographic and stroke characteristics, including stroke risk factors, neuroimaging, and acute stroke treatments, will be determined and documented. All participants will wear an accelerometer for one week at three different time-points (baseline, 6, and 12 weeks) to assess movement-related behaviours. Following randomization, participants in the intervention arm will receive a 'sit less, move more, sleep better' program for up to 1 hour/day, 5 days/week, for 6 weeks to enhance self-efficacy for change. Participants in the control arm will receive usual inpatient and early supported stroke discharge care. The feasibility outcomes will include reach (enrolled/eligible), retention (completed/enrolled), adverse events, and program adherence. Other outcomes at 6 and 12 weeks include the modified Rankin Scale, Timed-Up and Go, movement-related behaviours, walking endurance, gait speed, cognition, stroke severity and quality of life. Mixed-effects models will assess changes in outcomes over time. Compositional associations between movement-related behaviours and outcomes will consider covariates such as imaging markers. DISCUSSION: Adopting a whole-day approach to poststroke rehabilitation will provide valuable insights into the relationship between optimizing movement-related behaviours early after stroke and their impact on functional outcomes. Through exploring person-specific behavioural and imaging markers, this study may inform precision rehabilitation strategies, and guide clinical decision making for more tailored interventions. TRIAL REGISTRATION: Clinical Trial registration (ClinicalTrials.gov Identifier: NCT05753761, March 3, 2023).

Emotional dysmetria after cerebellar-pontine stroke: a case report.

INTRODUCTION: Pseudobulbar affect, or emotional dysregulation, commonly occurs following stroke. However, it is frequently missed in cases involving the cerebellum, resulting in a lack of treatment, which can directly impact stroke rehabilitation. CASE PRESENTATION: A 63-year-old Caucasian female with no history of mood disorders presented with gait instability, dysarthria, and right sided hemiplegia, secondary to cerebellar and pontine ischemic stroke from a basilar occlusion. She underwent endovascular therapy and her deficits gradually improved. However during recovery she began to develop uncontrollable tearfulness while retaining insight that her emotional expression was contextually inappropriate. She was treated with a selective serotonin reuptake inhibitor with reported improvements in her emotional regulation at one year follow up. CONCLUSION: This case highlights cerebellar injury as a potential cause of poorly regulated emotions, or an emotional dysmetria. The recognition of this disorder in patients with cerebellar or pontine strokes is critical, as untreated pseudobulbar affect can impact future stroke rehabilitation.

Sex Differences in Thrombin Generation in Patients with Acute Ischemic Stroke.

Sex differences in stroke exist, including variation in stroke risk and outcome. Differences in thrombin generation may contribute to this variation between females and males. To examine this, we assessed sex differences in thrombin generation between females and males with acute ischemic stroke and the relationship to blood cell gene expression. In 97 patients with acute ischemic stroke, thrombin generation was measured by thrombin generation assay. Blood cell gene expression was measured by microarray. Differences in thrombin generation between sexes were identified and the relationship to blood cell gene expression examined. Genes associated with sex differences in thrombin generation were analyzed by functional pathway analysis. Females and males had similar overall capacity to generate thrombin. The peak thrombin generated in females was 468.8 nM (SD 91.6), comparable to males (479.3nM;SD 90.8; p = 0.58). Lag time, time to peak thrombin, and endogenous thrombin potential were also similar between females and males. While overall thrombin generation was comparable between females and males with stroke, differences in genes that promote this thrombin generation exist. Females with high peak thrombin had an increase in genes that promote thrombosis, and platelet activation. In contrast, males with high peak thrombin had a decrease in genes involved in thrombus degradation. Females and males with acute ischemic stroke have similar capacity to generate thrombin, however, differences may exist in how this thrombin generation is achieved, with females having increased thrombin signaling, and platelet activation, and males having decreased thrombus degradation. This suggests regulatory differences in thrombosis may exist between females and males that may contribute to sex differences in stroke.

Reconsolidation of traumatic memories protocol compared to trauma-focussed cognitive behaviour therapy for post-traumatic stress disorder in UK military veterans: a randomised controlled feasibility trial.

BACKGROUND: Post-traumatic stress disorder (PTSD) occurs more commonly in military veterans than the general population. Whilst current therapies are effective, up to half of veterans commencing treatment do not complete it. Reconsolidation of Traumatic Memories (RTM) protocol is a novel, easy to train, talking therapy with promising findings. We examine the feasibility of undertaking an efficacy trial of RTM in veterans. METHODS: A parallel group, single-centre randomised controlled feasibility trial with a post-completion qualitative interview study. Sixty military veterans were randomised 2:1 to RTM (n = 35) or Trauma Focussed Cognitive Behaviour Therapy (CBT) (n = 25). We aimed to determine the rate of recruitment and retention, understand reasons for attrition, determine data quality and size of efficacy signal. We explored veterans' perceptions of experiences of joining the trial, the research procedures and therapy, and design improvements for future veteran studies. Military veterans with a diagnosis of PTSD or complex PTSD, and clinically significant symptoms, were recruited between January 2020 and June 2021. Primary outcome was feasibility using pre-determined progression criteria alongside PTSD symptoms, with depression, recovery, and rehabilitation as secondary outcomes. Data were collected at baseline, 6, 12, and 20 weeks. Interviews (n = 15) were conducted after 20 weeks. Both therapies were delivered by trained charity sector provider therapists. RESULTS: Participants' mean age was 53 years, the mean baseline PTSD symptoms score assessed by the Post-traumatic Stress Checklist (PCL-5) was 57 (range 0-80). Fifty had complex PTSD and 39 had experienced ≥ 4 traumas. Data were analysed at 20 weeks for feasibility outcomes (n = 60) and mental health outcomes (n = 45). Seven of eight progression criteria were met. The RTM group experienced a mean 18-point reduction on the PCL-5. TFCBT group participants experienced a mean reduction of eight points. Forty-eight percent of the RTM group no longer met diagnostic criteria for PTSD compared to 16% in the TFCBT group. All veterans reported largely positive experiences of the therapy and research procedures and ways to improve them. CONCLUSION: RTM therapy remains a promising psychological intervention for the treatment of PTSD, including complex PTSD, in military veterans. With specific strengthening, the research protocol is fit for purpose in delivering an efficacy trial. TRIAL REGISTRATION: ISRCTN registration no 10314773 on 01.10.2019. Full trial protocol: available on request or downloadable at ISRCTN reg. no. 10314773.

A Glycolipidated-liposomal peptide vaccine confers long-term mucosal protection against Streptococcus pyogenes via IL-17, macrophages and neutrophils.

Mucosally active subunit vaccines are an unmet clinical need due to lack of licensed immunostimulants suitable for vaccine antigens. Here, we show that intranasal administration of liposomes incorporating: the Streptococcus pyogenes peptide antigen, J8; diphtheria toxoid as a source of T cell help; and the immunostimulatory glycolipid, 3D(6-acyl) PHAD (PHAD), is able to induce long-lived humoral and cellular immunity. Mice genetically deficient in either mucosal antibodies or total antibodies are protected against S. pyogenes respiratory tract infection. Utilizing IL-17-deficient mice or depleting cellular subsets using antibodies, shows that the cellular responses encompassing, CD4+ T cells, IL-17, macrophages and neutrophils have important functions in vaccine-mediated mucosal immunity. Overall, these data demonstrate the utility of a mucosal vaccine platform to deliver multi-pronged protective responses against a highly virulent pathogen.

Hyperbaric oxygen therapy for late radiation tissue injury.

BACKGROUND: This is the third update of the original Cochrane Review published in July 2005 and updated previously in 2012 and 2016. Cancer is a significant global health issue. Radiotherapy is a treatment modality for many malignancies, and about 50% of people having radiotherapy will be long-term survivors. Some will experience late radiation tissue injury (LRTI), developing months or years following radiotherapy. Hyperbaric oxygen therapy (HBOT) has been suggested as a treatment for LRTI based on the ability to improve the blood supply to these tissues. It is postulated that HBOT may result in both healing of tissues and the prevention of complications following surgery and radiotherapy. OBJECTIVES: To evaluate the benefits and harms of hyperbaric oxygen therapy (HBOT) for treating or preventing late radiation tissue injury (LRTI) compared to regimens that excluded HBOT. SEARCH METHODS: We used standard, extensive Cochrane search methods. The latest search date was 24 January 2022. SELECTION CRITERIA: We included randomised controlled trials (RCTs) comparing the effect of HBOT versus no HBOT on LRTI prevention or healing. DATA COLLECTION AND ANALYSIS: We used standard Cochrane methods. Our primary outcomes were 1. survival from time of randomisation to death from any cause; 2. complete or substantial resolution of clinical problem; 3. site-specific outcomes; and 4. ADVERSE EVENTS: Our secondary outcomes were 5. resolution of pain; 6. improvement in quality of life, function, or both; and 7. site-specific outcomes. We used GRADE to assess certainty of evidence. MAIN RESULTS: Eighteen studies contributed to this review (1071 participants) with publications ranging from 1985 to 2022. We added four new studies to this updated review and evidence for the treatment of radiation proctitis, radiation cystitis, and the prevention and treatment of osteoradionecrosis (ORN). HBOT may not prevent death at one year (risk ratio (RR) 0.93, 95% confidence interval (CI) 0.47 to 1.83; I2 = 0%; 3 RCTs, 166 participants; low-certainty evidence). There is some evidence that HBOT may result in complete resolution or provide significant improvement of LRTI (RR 1.39, 95% CI 1.02 to 1.89; I2 = 64%; 5 RCTs, 468 participants; low-certainty evidence) and HBOT may result in a large reduction in wound dehiscence following head and neck soft tissue surgery (RR 0.24, 95% CI 0.06 to 0.94; I2 = 70%; 2 RCTs, 264 participants; low-certainty evidence). In addition, pain scores in ORN improve slightly after HBOT at 12 months (mean difference (MD) -10.72, 95% CI -18.97 to -2.47; I2 = 40%; 2 RCTs, 157 participants; moderate-certainty evidence). Regarding adverse events, HBOT results in a higher risk of a reduction in visual acuity (RR 4.03, 95% CI 1.65 to 9.84; 5 RCTs, 438 participants; high-certainty evidence). There was a risk of ear barotrauma in people receiving HBOT when no sham pressurisation was used for the control group (RR 9.08, 95% CI 2.21 to 37.26; I2 = 0%; 4 RCTs, 357 participants; high-certainty evidence), but no such increase when a sham pressurisation was employed (RR 1.07, 95% CI 0.52 to 2.21; I2 = 74%; 2 RCTs, 158 participants; high-certainty evidence). AUTHORS' CONCLUSIONS: These small studies suggest that for people with LRTI affecting tissues of the head, neck, bladder and rectum, HBOT may be associated with improved outcomes (low- to moderate-certainty evidence). HBOT may also result in a reduced risk of wound dehiscence and a modest reduction in pain following head and neck irradiation. However, HBOT is unlikely to influence the risk of death in the short term. HBOT also carries a risk of adverse events, including an increased risk of a reduction in visual acuity (usually temporary) and of ear barotrauma on compression. Hence, the application of HBOT to selected participants may be justified. The small number of studies and participants, and the methodological and reporting inadequacies of some of the primary studies included in this review demand a cautious interpretation. More information is required on the subset of disease severity and tissue type affected that is most likely to benefit from this therapy, the time for which we can expect any benefits to persist and the most appropriate oxygen dose. Further research is required to establish the optimum participant selection and timing of any therapy. An economic evaluation should also be undertaken.

Variable resistance to zinc intoxication among Streptococcus agalactiae reveals a novel IS1381 insertion element within the zinc efflux transporter gene czcD.

Streptococcus agalactiae, also known as group B Streptococcus, is an important human and animal pathogen. Zinc (Zn) is an essential trace element for normal bacterial physiology but intoxicates bacteria at high concentrations. Molecular systems for Zn detoxification exist in S. agalactiae, however the degree to which Zn detoxification may vary among different S. agalactiae isolates is not clear. We measured resistance to Zn intoxication in a diverse collection of clinical isolates of S. agalactiae by comparing the growth of the bacteria in defined conditions of Zn stress. We found significant differences in the ability of different S. agalactiae isolates to resist Zn intoxication; some strains such as S. agalactiae 18RS21 were able to survive and grow at 3.8-fold higher levels of Zn stress compared to other reference strains such as BM110 (6.4mM vs 1.68mM Zn as inhibitory, respectively). We performed in silico analysis of the available genomes of the S. agalactiae isolates used in this study to examine the sequence of czcD, which encodes an efflux protein for Zn that supports resistance in S. agalactiae. Interestingly, this revealed the presence of a mobile insertion sequence (IS) element, termed IS1381, in the 5' region of czcD in S. agalactiae strain 834, which was hyper-resistant to Zn intoxication. Interrogating a wider collection of S. agalactiae genomes revealed identical placement of IS1381 in czcD in other isolates from the clonal-complex-19 (CC19) 19 lineage. Collectively, these results show a resistance spectrum among S. agalactiae isolates enables survival in varying degrees of Zn stress, and this phenotypic variability has implications for understanding bacterial survival in metal stress.

A Review of Successes and Impeding Challenges of IoT-Based Insect Pest Detection Systems for Estimating Agroecosystem Health and Productivity of Cotton.

Using artificial intelligence (AI) and the IoT (Internet of Things) is a primary focus of applied engineering research to improve agricultural efficiency. This review paper summarizes the engagement of artificial intelligence models and IoT techniques in detecting, classifying, and counting cotton insect pests and corresponding beneficial insects. The effectiveness and limitations of AI and IoT techniques in various cotton agricultural settings were comprehensively reviewed. This review indicates that insects can be detected with an accuracy of between 70 and 98% using camera/microphone sensors and enhanced deep learning algorithms. However, despite the numerous pests and beneficial insects, only a few species were targeted for detection and classification by AI and IoT systems. Not surprisingly, due to the challenges of identifying immature and predatory insects, few studies have designed systems to detect and characterize them. The location of the insects, sufficient data size, concentrated insects on the image, and similarity in species appearance are major obstacles when implementing AI. Similarly, IoT is constrained by a lack of effective field distance between sensors when targeting insects according to their estimated population size. Based on this study, the number of pest species monitored by AI and IoT technologies should be increased while improving the system's detection accuracy.