Inositol for Polycystic Ovary Syndrome: A Systematic Review and Meta-analysis to Inform the 2023 Update of the International Evidence-based PCOS Guidelines.

CONTEXT: Insulin resistance is common in women with polycystic ovary syndrome (PCOS). Inositol may have insulin sensitizing effects; however, its efficacy in the management of PCOS remains indeterminate. OBJECTIVE: To inform the 2023 international evidence-based guidelines in PCOS, this systematic review and meta-analysis evaluated the efficacy of inositol, alone or in combination with other therapies, in the management of PCOS. DATA SOURCES: Medline, PsycInfo, EMBASE, All EBM, and CINAHL from inception until August 2022. STUDY SELECTION: Thirty trials (n = 2230; 1093 intervention, 1137 control), with 19 pooled in meta-analyses were included. DATA EXTRACTION: Data were extracted for hormonal, metabolic, lipids, psychological, anthropometric, reproductive outcomes, and adverse effects by 1 reviewer, independently verified by a second. DATA SYNTHESIS: Thirteen comparisons were assessed, with 3 in meta-analyses. Evidence suggests benefits for myo-inositol or D-chiro-inositol (DCI) for some metabolic measures and potential benefits from DCI for ovulation, but inositol may have no effect on other outcomes. Metformin may improve waist-hip ratio and hirsutism compared to inositol, but there is likely no difference for reproductive outcomes, and the evidence is very uncertain for body mass indexI. Myo-inositol likely causes fewer gastrointestinal adverse events compared with metformin; however, these are typically mild and self-limited. CONCLUSION: The evidence supporting the use of inositol in the management of PCOS is limited and inconclusive. Clinicians and their patients should consider the uncertainty of the evidence together with individual values and preferences when engaging in shared decision-making regarding the use of inositol for PCOS.

Normative Data on Serum and Plasma Tryptophan and Kynurenine Concentrations from 8089 Individuals Across 120 Studies: A Systematic Review and Meta-Analysis.

In this systematic review and meta-analysis, a normative dataset is generated from the published literature on the kynurenine pathway in control participants extracted from case-control and methodological validation studies. Study characteristics were mapped, and studies were evaluated in terms of analytical rigour and methodological validation. Meta-analyses of variance between types of instruments, sample matrices and metabolites were conducted. Regression analyses were applied to determine the relationship between metabolite, sample matrix, biological sex, participant age and study age. The grand mean concentrations of tryptophan in the serum and plasma were 60.52 ± 15.38 µM and 51.45 ± 10.47 µM, respectively. The grand mean concentrations of kynurenine in the serum and plasma were 1.96 ± 0.51 µM and 1.82 ± 0.54 µM, respectively. Regional differences in metabolite concentrations were observed across America, Asia, Australia, Europe and the Middle East. Of the total variance within the data, mode of detection (MOD) accounted for up to 2.96%, sample matrix up to 3.23%, and their interaction explained up to 1.53%; the latter of which was determined to be negligible. This review was intended to inform future empirical research and method development studies and successfully synthesised pilot data. The pilot data reported in this study will inform future precision medicine initiatives aimed at targeting the kynurenine pathway by improving the availability and quality of normative data.

Brain function effects of exercise interventions for cognitive decline: a systematic review and meta-analysis.

Introduction: Exercise is recognized as a modifiable lifestyle factor that can mitigate cognitive decline and dementia risk. While the benefits of exercise on cognitive aging have been reported on extensively, neuronal effects in adults experiencing cognitive decline have not been systematically synthesized. The aim of this systematic review was to assess the effects of exercise on cognition and brain function in people with cognitive decline associated with dementia risk. Method: A systematic search was conducted for randomized controlled trials of ≥ 4 weeks exercise (aerobic, resistance, or mind-body) that assessed cognition and brain function using neuroimaging and neurophysiological measures in people with subjective or objective cognitive decline. Study characteristics and brain function effects were narratively synthesized, while domain-specific cognitive performance was subjected to meta-analysis. Study quality was also assessed. Results: 5,204 records were identified and 12 unique trials met the eligibility criteria, representing 646 adults classified with cognitive frailty, mild or vascular cognitive impairment. Most interventions involved 40-minute sessions conducted 3 times/week. Exercise improved global cognition (g = -0.417, 95% CI, -0.694 to -0.140, p = 0.003, I2 = 43.56%), executive function (g = -0.391, 95% CI, -0.651 to -0.131, p = 0.003, I2 = 13.28%), but not processing speed or general short-term memory (both p >0.05). Across fMRI and ERP studies, significant neuronal adaptations were found with exercise cf. control throughout the brain and were linked with improved global cognition, memory, and executive function. Cerebral blood flow was also found to improve with 24 weeks of exercise, but was not linked with cognitive changes. Discussion: The cognitive improvements associated with exercise are likely driven by increased metabolic activity, cerebrovascular mechanisms, and neuroplasticity throughout the brain. Our paper shows the promise in, and need for, high-quality trials integrating cognitive and brain function measures to elucidate the functional relationship between exercise and brain health in populations with a high risk of dementia. Systematic review registration: PROSPERO, identifier: CRD42022291843.

Vaccines against chicken coccidiosis with particular reference to previous decade: progress, challenges, and opportunities.

Chicken coccidiosis is an economically significant disease of commercial chicken industry accounting for losses of more than £10.4 billion (according to 2016 prices). Additionally, the costs incurred in prophylaxis and therapeutics against chicken coccidiosis in developing countries (for instance Pakistan according to 2018 prices) reached US $45,000.00 while production losses for various categories of chicken ranges 104.74 to US $2,750,779.00. The infection has been reported from all types of commercial chickens (broiler, layer, breeder) having a range of reported prevalence of 7-90%. The concern of resistance towards major anticoccidials has provided a way forward to vaccine research and development. For prophylaxis of chicken coccidiosis, live virulent, attenuated, ionophore tolerant strains and recombinant vaccines have been extensively trialed and commercialized. Eimeria antigens and novel vaccine adjuvants have elicited the protective efficacy against coccidial challenge. The cost of production and achieving robust immune responses in birds are major challenges for commercial vaccine production. In the future, research should be focused on the development of multivalent anticoccidial vaccines for commercial poultry. Efforts should also be made on the discovery of novel antigens for incorporation into vaccine designs which might be more effective against multiple Eimeria species. This review presents a recap to the overall progress against chicken Eimeria with particular reference to previous decade. The article presents critical analysis of potential areas for future research in chicken Eimeria vaccine development.

Automated Tissue Strain Calculations Using Harris Corner Detection.

The elastic modulus, or slope of the stress-strain curve, is an important metric for evaluating tissue functionality, particularly for load-bearing tissues such as tendon. The applied force can be tracked directly from a mechanical testing system and converted to stress using the tissue cross-sectional area; however, strain can only be calculated in post-processing by tracking tissue displacement from video collected during mechanical testing. Manual tracking of Verhoeff stain lines pre-marked on the tissue is time-consuming and highly dependent upon the user. This paper details the development and testing of an automated processing method for strain calculations using Harris corner detection. The automated and manual methods were compared in a dataset consisting of 97 rat tendons (48 Achilles tendons, 49 supraspinatus tendons), divided into ten subgroups for evaluating the effects of different therapies on tendon mechanical properties. The comparison showed that average percent differences between the approaches were 0.89% and -2.10% for Achilles and supraspinatus tendons, respectively. The automated approach reduced processing time by 83% and produced similar results to the manual method when comparing the different subgroups. This automated approach to track tissue displacements and calculate elastic modulus improves post-processing time while simultaneously minimizing user dependency.

Effects of focused ultrasound and dry needling on tendon mechanical properties.

Tendon injuries are extremely common, resulting in mechanically weaker tendons that could lead to tendon rupture. Dry needling (DN) is widely used to manage pain and function after injury. However, DN is invasive and high inter-practitioner variability has led to mixed success rates. Focused ultrasound (fUS) is a non-invasive medical technology that directs ultrasound energy into a well-defined focal volume. fUS can induce thermal ablation or mechanical fractionation, with bioeffect type controlled through ultrasound parameters. Tendons must withstand high physiological loads, thus treatments maintaining tendon mechanical properties while promoting healing are needed. Our objective was to evaluate mechanical effects of DN and 3 fUS parameter sets, chosen to prioritize mechanical fractionation, on Achilles and supraspinatus tendons. Ex vivo rat Achilles and supraspinatus tendons (50 each) were divided into sham, DN, fUS-1, fUS-2, and fUS-3 (n = 10/group). Following treatment, tendons were mechanically tested. Elastic modulus of supraspinatus tendons treated with DN (126.64 ± 28.1 MPa) was lower than sham (153.02 ± 29.3 MPa; p = 0.0280). Stiffness and percent relaxation of tendons treated with DN (Achilles: 114.40 ± 31.6 N/mm; 49.10 ± 6.1%; supraspinatus: 109.53 ± 30.8 N/mm; 50.17 ± 7.6%) were lower (all p < 0.0334) than sham (Achilles: 141.34 ± 20.9 N/mm; 60.30 ± 7.7%; supraspinatus: 135.14 ± 30.2 N/mm; 60.85 ± 15.4%). Modulus of Achilles and supraspinatus tendons treated with fUS-1 (159.88 ± 25.7 MPa; 150.12 ± 22.0 MPa, respectively) were similar to sham (156.35 ± 23.0 MPa; 153.02 ± 29.3 MPa, respectively). These results suggest that fUS preserves mechanical properties better than DN, with fUS-1 performing better than fUS-2 and fUS-3. fUS should be studied further to fully understand its mechanical and healing effects to help evaluate fUS as an alternative, non-invasive treatment for tendon injuries.

Focused Ultrasound Mechanical Disruption of Ex Vivo Rat Tendon.

Around 30 million tendon injuries occur annually in the U.S. costing $ 114 billion. Conservative therapies, like dry needling, promote healing in chronically injured tendons by inducing microdamage but have mixed success rates. Focused ultrasound (fUS) therapy can noninvasively fractionate tissues through the creation, oscillation, and collapse of bubbles in a process termed histotripsy; however, highly collagenous tissues, like tendon, have shown resistance to mechanical fractionation. This study histologically evaluates whether fUS mechanical disruption is achievable in tendons. Ex vivo rat tendons (45 Achilles and 44 supraspinatus) were exposed to 1.5-MHz fUS operating with 0.1-10 ms pulses repeated at 1-100 Hz for 15-60 s with peak positive pressures <89 MPa and peak negative pressures <26 MPa; other tendons were exposed to dry needling or sham. Immediately after treatment, tendons were flash-frozen and stained with hematoxylin and eosin (H&E) or alpha-nicotinamide adenine dinucleotide diaphorase ( α -NADH-d) and evaluated by two reviewers blinded to the exposure conditions. Results showed successful creation of bubbles for all fUS-treated samples; however, not all samples showed histological injury. When the injury was detected, parameter sets with shorter pulses (0.1-1 ms), lower acoustic pressures, or reduced treatment times showed mechanical disruption in the form of fiber separation and fraying with little to no thermal injury. Longer pulses or treatment times showed a combination of mechanical and thermal injury. These findings suggest that mechanical disruption is achievable in tendons within a small window of acoustic parameters, supporting the potential of fUS therapy in tendon treatment.

An accelerated framework for the classification of biological targets from solid-state micropore data.

Micro- and nanoscale systems have provided means to detect biological targets, such as DNA, proteins, and human cells, at ultrahigh sensitivity. However, these devices suffer from noise in the raw data, which continues to be significant as newer and devices that are more sensitive produce an increasing amount of data that needs to be analyzed. An important dimension that is often discounted in these systems is the ability to quickly process the measured data for an instant feedback. Realizing and developing algorithms for the accurate detection and classification of biological targets in realtime is vital. Toward this end, we describe a supervised machine-learning approach that records single cell events (pulses), computes useful pulse features, and classifies the future patterns into their respective types, such as cancerous/non-cancerous cells based on the training data. The approach detects cells with an accuracy of 70% from the raw data followed by an accurate classification when larger training sets are employed. The parallel implementation of the algorithm on graphics processing unit (GPU) demonstrates a speedup of three to four folds as compared to a serial implementation on an Intel Core i7 processor. This incredibly efficient GPU system is an effort to streamline the analysis of pulse data in an academic setting. This paper presents for the first time ever, a non-commercial technique using a GPU system for realtime analysis, paired with biological cluster targeting analysis.

GPU-based real-time detection and analysis of biological targets using solid-state nanopores.

The emergence of nanoscale devices has provided robust interfaces to biomolecules that faithfully transduce and define fundamental interactions of living systems. Measuring single-event behavior of important targets like DNA, and diseased cells has been achieved with a number of devices and systems. An important dimension to these systems, often discounted, is real-time computational decision-making from measured data. This paper describes an adaptive approach that can record single-molecule or single-cell events in real-time and automatically analyze patterns from the measured data. The automated analysis of measured data is done using a static threshold technique and two variations of a dynamic threshold technique: baseline-tracker and moving average filtering. Dynamic techniques for threshold detection enable noise suppression in the measured data and precise detection of patterns, but at the cost of more complex software as compared to static technique. To mitigate the computational overhead, a real-time system is implemented that uses advanced I/O techniques to minimize the execution stalls, thus enabling the system to process data significantly faster than the electrical measurement setup. Furthermore, the algorithms are implemented on programmable graphics processing units for parallel pattern detection. Our implementation provides five times faster data acquisition and pattern detection than the maximum sampling rate of the electrical measurement setup.