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Limbic-predominant age-related TDP-43 encephalopathy (LATE) affects approximately one-third of older individuals and is associated with cognitive impairment. However, there is a highly incomplete understanding of the genetic determinants of LATE neuropathologic changes (LATE-NC) in diverse populations. The defining neuropathologic feature of LATE-NC is TDP-43 proteinopathy, often with comorbid hippocampal sclerosis (HS). In terms of genetic risk factors, LATE-NC and/or HS are associated with single nucleotide variants (SNVs) in 3 genes-TMEM106B (rs1990622), GRN (rs5848), and ABCC9 (rs1914361 and rs701478). We evaluated these 3 genes in convenience samples of individuals of African ancestry. The allele frequencies of the LATE-associated alleles were significantly different between persons of primarily African (versus European) ancestry: In persons of African ancestry, the risk-associated alleles for TMEM106B and ABCC9 were less frequent, whereas the risk allele in GRN was more frequent. We performed an exploratory analysis of data from African-American subjects processed by the Alzheimer's Disease Genomics Consortium, with a subset of African-American participants (n = 166) having corroborating neuropathologic data through the National Alzheimer's Coordinating Center (NACC). In this limited-size sample, the ABCC9/rs1914361 SNV was associated with HS pathology. More work is required concerning the genetic factors influencing non-Alzheimer disease pathology such as LATE-NC in diverse cohorts.

Patients these days are increasingly conscious of personal appearance, and much attention is being focused on the smile. Cosmetic dentistry is also in the race to become the most advanced and demanding dental subspecialty. Recently, aesthetic lip surgeries have been introduced, like lip repositioning, lip reduction and lip enhancement surgeries, to improve facial aesthetics. The authors present a case of a 28-year-old healthy male who reported to the Department of Periodontics with the chief complaint of poor aesthetics and large lips. His lower lip was double the size of the upper lip. Therefore, an aesthetic lip reduction surgery was planned. The lip reduction operation could successfully manage the large lower lip with no intra or postoperative complications. No recurrence was observed within a period of 12 months. Cheiloplasty balances the look of the top and lower lips, improving the appearance of the face as a whole.

IntroductionAlzheimer’s Disease (AD) typically starts in the medial temporal lobe, then develops into a neurodegenerative cascade which spreads to other brain regions. People with subjective cognitive decline (SCD) are more likely to develop dementia, especially in the presence of amyloid pathology. Thus, we were interested in the white matter microstructure of the medial temporal lobe in SCD, specifically the lower cingulum bundle that leads into the hippocampus. Diffusion tensor imaging (DTI) has been shown to differentiate SCD participants who will progress to mild cognitive impairment from those who will not. However, the biology underlying these DTI metrics is unclear, and results in the medial temporal lobe have been inconsistent.MethodsTo better characterize the microstructure of this region, we applied DTI to cognitively normal participants in the Cam-CAN database over the age of 55 with cognitive testing and diffusion MRI available (N = 325, 127 SCD). Diffusion MRI was processed to generate regional and voxel-wise diffusion tensor values in bilateral lower cingulum white matter, while T1-weighted MRI was processed to generate regional volume and cortical thickness in the medial temporal lobe white matter, entorhinal cortex, temporal pole, and hippocampus.ResultsSCD participants had thinner cortex in bilateral entorhinal cortex and right temporal pole. No between-group differences were noted for any of the microstructural metrics of the lower cingulum. However, correlations with delayed story recall were significant for all diffusion microstructure metrics in the right lower cingulum in SCD, but not in controls, with a significant interaction effect. Additionally, the SCD group showed an accelerated aging effect in bilateral lower cingulum with MD, AxD, and RD.DiscussionThe diffusion profiles observed in both interaction effects are suggestive of a mixed neuroinflammatory and neurodegenerative pathology. Left entorhinal cortical thinning correlated with decreased FA and increased RD, suggestive of demyelination. However, right entorhinal cortical thinning also correlated with increased AxD, suggestive of a mixed pathology. This may reflect combined pathologies implicated in early AD. DTI was more sensitive than cortical thickness to the associations between SCD, memory, and age. The combined effects of mixed pathology may increase the sensitivity of DTI metrics to variations with age and cognition.

Regenerating periodontal tissue is the main goal of periodontal therapy. Periodontal tissue regeneration involves the development of new bone, cement, and periodontal ligaments on damaged tooth root surfaces in order to restore anatomy and function. In order to further enhance PRF (Platelet rich fibrin) and develop advanced platelet-rich fibrin, a slower rotating speed is proposed (A-PRFs). Cell dispersion is affected by centrifugation rate. The majority of the leukocytes in the PRF are concentrated near the bottom of the tube due to centrifugation rate. By switching the centrifugation process to 1,500 rpm for 14 minutes, granulocyte neutrophils and the fibrin matrix are more evenly distributed in the A-PRF created. Hence, a periodontal evaluation of this subject is required.

Households, restaurants, canteens, and hotel wastes constitute kitchen waste. Every day our growing cities generate more and more waste, which is overloading our municipal systems. The main aim of the present work was to prepare a microbial consortium that can effectively and rapidly bring about the degradation of kitchen wastes that can be used in agricultural soils. More than 100 different bacterial isolates were obtained from various kitchen waste dumping areas. The bacterial isolates were studied to produce enzymes like amylase, gelatinase, lipase, and protease on respective media plates. The best 20 isolates were subjected to enzyme quantification. The isolates showing maximum production for all four enzymes were selected for consortia preparation. The consortia of isolates were prepared by permutation combinations. Amongst all consortia prepared consortium No. 7 showed maximum enzymatic potential. The bacterial isolates in the best consortium (No. 7) were further characterized and identified as KW104 Serratia marcescens, KW37 Micrococcus luteus, KW128 Brevindimonas mediterranea, KW91 Bacillus tequilensis, and KW97 Exiguobacterium mexicanum. This consortium showed rapid degradation of waste as compared to others in 15 days duration of time showing good potential for compost formation when applied to plant growth.

False smut of rice (Oryza sativa L.) caused by Ustilaginoidea virens (Cooke) Takah., 1896 is an important emerging disease of rice. An experiment was conducted during 2018–19 and 2019–20 at Institute of Agricultural Sciences, Banaras Hindu University, Varanasi, Uttar Pradesh to study the U. virens prevalence and morphological variability in northern India with the effect of weather variables on the percentage disease incidence (PDI) of false smut of rice. The study revealed that the false smut incidence was higher in Varanasi district of Uttar Pradesh (53.64%). The lowest percentage (20.68–27.55%) of infected tillers was found in Kangra district of Himachal Pradesh, and Tehri Garhwal district of Uttarakhand. The grain replacement percentage was highest in the Moti cultivar (51.17%), while the highest yield loss percentage was in the Pusa Basmati (57.11 %) variety. The majority of the isolates in our investigation had fluffy, raised, and irregular colony morphology. The correlation between the false smut disease incidence and weather has been evaluated in the Varanasi district, and found that the temperature of 20.36°C with an RH of 85.13% and low rainfall of 8.92 mm was conducive to disease initiation and positively correlated with the PDI. Other epiphytotic factors like sunshine hours, and wind speed were all found to be negatively linked with PDI. In this investigation, for the first time, the viability of spores was also checked. It was found that 2-year-old spores were not viable because they did not retain any Brilliant Cresyl blue colour dye, which stains the stored food material in spores, while 1-month-old spores were found to be 100% viable. All the isolates were further confirmed with the specific ITS marker.

The aye-aye (Daubentonia madagascariensis) is a nocturnal lemur native to the island of Madagascar with a unique thin middle finger. Its slender third digit has a remarkably specific adaptation, allowing them to perform tap-scanning to locate small cavities beneath tree bark and extract wood-boring larvae from it. As an exceptional active acoustic actuator, this finger makes an aye-aye’s biological system an attractive model for pioneering Nondestructive Evaluation (NDE) methods and robotic systems. Despite the important aspects of the topic in the aye-aye’s unique foraging and its potential contribution to the engineering sensory, little is known about the mechanism and dynamics of this unique finger. This paper used a motion-tracking approach for the aye-aye’s middle finger using simultaneous video graphic capture. To mimic the motion, a two-link robot arm model is designed to reproduce the trajectory. Kinematics formulations were proposed to derive the motion of the middle finger using the Lagrangian method. In addition, a hardware model was developed to simulate the aye-aye’s finger motion. To validate the model, different motion states such as trajectory paths and joint angles, were compared. The simulation results indicate the kinematics of the model were consistent with the actual finger movement. This model is used to understand the aye-aye’s unique tap-scanning process for pioneering new tap-testing NDE strategies for various inspection applications.

Dental implant treatment is turning into a widely accepted and popular treatment option for patients. With the growing era of dental implant therapy, complications and failures have also become common. Such intricacies are becoming a vexing issue for clinicians as well as patients. Implant failures can be due to mechanical or biological reasons. Failure of osseointegration of the implant falls under biological failures, whereas mechanical complications include fracture of the implant, framework or prosthetic components. Diligently observing the implant after placement is the first step in managing the declining circumstances. It is important to have a thorough understanding of how and why implants fail to achieve successful treatment outcomes in the long run. In dentistry, nanoparticles are used to make antibacterial chemicals that improve dental implants. They can be used in conjunction with acrylic resins for fabricating removable dentures during prosthetic treatments, composite resins for direct restoration during restorative treatments, endodontic irrigants and obturation materials during endodontic procedures, orthodontic adhesives and titanium coating during dental implant procedures. This article aimed to review the etiological factors that lead to implant failure and their solutions.

Growth promoting Rhizobium spp are frequently used as biofertilizers for agricultural cropping system. Furthermore, Isolation, screening and biochemical characterization of Rhizobium for a specific plant is necessary to examine ability of isolated bacteria to affect the growth and development of host plant in various ways. The current study was aimed to isolate plant specific rhizobacterial strains which are compatible with lentil (Lens culinaris Medik.L.) plant. 20 bacterial isolates have been isolated from root nodules of lentil from various agro ecological area and their biochemical characterization was performed by different plant growth promotion activities. The result showed that, among 20 isolates, four isolates have vigorous plant growth promoting activities. Four bacterial strains were able to solubilise phosphorous along with hormone production. Moreover, among four bacterial strains, two strongly produced HCN and siderophore in vitro. Subsequently, all selected bacterial isolates were inoculated in lentil seeds of variety HUL57 to study germination percentage and vigour index of the crop. Out of four isolates 26N isolate performed best growth promotion activities on lentil seedlings. Finally, on the basis of performance of bacteria on plant, four isolates were characterized using molecular approach of species identification such as 16S rRNA sequencing.

Introduction Dark colored gingiva is an esthetic concern that cannot be ignored, especially when accompanied by a high lip line or gummy smile. Gingival depigmentation is a periodontal plastic surgical procedure wherein the hyperpigmentation is removed or reduced by various techniques. Protecting the wound from mechanical trauma and stability of the surgical site during the healing process are among the most important advantages of periodontal dressing application after surgery. Aim This study is aimed to comparatively evaluate the effectiveness of reactive oxygen gel species (BlueM gel) and the traditional Coe-Pack dressing on gingival healing and pain after surgical depigmentation. Protocol This split-mouth randomized clinical trial will be conducted on 20 patients aged 18–45 years with maxillary physiologic gingival pigmentation classes (II) (III) and (IV) according to the Dummett–Gupta Oral Pigmentation Index (40 treated sites). The maxilla will be randomly divided into two symmetrical parts—from the right second premolar to the midline and from the midline to the left second premolar—to receive either BlueM gel or Coe- Pack as a dressing after surgical depigmentation with a scalpel. Various indices will be assessed, such as plaque index, papillary bleeding index, pain index, healing index and reepithelization index with toluidine blue, and the follow-up period will be one month. Expected results- A total of 20 patients will be included in this study. Statistically significant differences are expected to show in the pain index and healing index after one, two, three, four, and five days. The BlueM gel group is expected to show a higher significant difference after one, two, three and four weeks in the reepithelization index.

GABAergic inhibitory neurons are the principal source of inhibition in the brain. Traditionally, their role in maintaining the balance of excitation-inhibition has been emphasized. Beyond homeostatic functions, recent circuit mapping and functional manipulation studies have revealed a wide range of specific roles that GABAergic circuits play in dynamically tilting excitation-inhibition coupling across spatio-temporal scales. These span from gating of compartment- and input-specific signaling, gain modulation, shaping input–output functions and synaptic plasticity, to generating signal-to-noise contrast, defining temporal windows for integration and rate codes, as well as organizing neural assemblies, and coordinating inter-regional synchrony. GABAergic circuits are thus instrumental in controlling single-neuron computations and behaviorally-linked network activity. The activity dependent modulation of sensory and mnemonic information processing by GABAergic circuits is pivotal for the formation and maintenance of episodic memories in the hippocampus. Here, we present an overview of the local and long-range GABAergic circuits that modulate the dynamics of excitation-inhibition and disinhibition in the main output area of the hippocampus CA1, which is crucial for episodic memory. Specifically, we link recent findings pertaining to GABAergic neuron molecular markers, electrophysiological properties, and synaptic wiring with their function at the circuit level. Lastly, given that area CA1 is particularly impaired during early stages of Alzheimer’s disease, we emphasize how these GABAergic circuits may contribute to and be involved in the pathophysiology.

Purpose: In Dynamic contrast-enhanced MRI (DCE-MRI), Arterial Input Function (AIF) has been shown to be a significant contributor to uncertainty in the estimation of kinetic parameters. This study is to assess the feasibility of using a deep learning network to estimate local Capillary Input Function (CIF) to estimate blood-brain barrier (BBB) permeability, while reducing the required scan time. Materials and Method: A total of 13 healthy subjects (younger ( 67 y/o): 5) were recruited and underwent 25-min DCE-MRI scans. The 25 min data were retrospectively truncated to 10 min to simulate a reduced scan time of 10 min. A deep learning network was trained to predict the CIF using simulated tissue contrast dynamics with two vascular transport models. The BBB permeability (PS) was measured using 3 methods: (i) Ca-25min, using DCE-MRI data of 25 min with individually sampled AIF (Ca); (ii) Ca-10min, using truncated 10min data with AIF (Ca); and (iii) Cp-10min, using truncated 10 min data with CIF (Cp). The PS estimates from the Ca-25min method were used as reference standard values to assess the accuracy of the Ca-10min and Cp-10min methods in estimating the PS values. Results: When compared to the reference method(Ca-25min), the Ca-10min and Cp-10min methods resulted in an overestimation of PS by 217 ± 241 % and 48.0 ± 30.2 %, respectively. The Bland Altman analysis showed that the mean difference from the reference was 8.85 ± 1.78 (x10−4 min−1) with the Ca-10min, while it was reduced to 1.63 ± 2.25 (x10−4 min−1) with the Cp-10min, resulting in an average reduction of 81%. The limits of agreement also reduced by up to 39.2% with the Cp-10min. We found a 75% increase of BBB permeability in the gray matter and a 35% increase in the white matter, when comparing the older group to the younger group. Conclusions: We demonstrated the feasibility of estimating the capillary-level input functions using a deep learning network. We also showed that this method can be used to estimate subtle age-related changes in BBB permeability with reduced scan time, without compromising accuracy. Moreover, the trained deep learning network can automatically select CIF, reducing the potential uncertainty resulting from manual user-intervention.

Introduction: Periodontitis is a chronic, multifactorial, inflammatory disease that leads to gradual loss of bone and periodontal attachment. Thus, periodontal surgery is required according to severity of diseases. The goal of periodontal reconstructive surgery is to regenerate soft and hard tissues destroyed during periodontal disease. Aim: To compare the effectiveness of bioresorbable collagen membrane in combination with Deproteinized Bovine Bone Matrix xenograft (group A); and Advanced Plasma rich fibrin(A-PRF) membrane in combination with Deproteinized Bovine Bone Matrix xenograft (group B) in the treatment of human infrabony defects. Methods: This randomised controlled trial will be carried out at the periodontics outpatient department. We will choose 24 patients with moderate to advanced chronic periodontitis who are otherwise systemically healthy. Infrabony defects will be treated by open flap debridement using bovine-derived xenograft and bioresorbable collagen membrane (group A) and open flap debridement using bovine-derived xenograft and A-PRF after the completion of first therapy (group B). At baseline and six months after undergoing periodontal surgery, probing pocket depth, clinical attachment level, radiographic bone fill, gingival recession, oral hygiene status, and gingival health will be measured. Expected results: It is suggested that Bioresorbable Collagen Membrane in combination with Deproteinized Bovine Bone Matrix xenograft will show better results as compared to Advanced Platelet Rich Fibrin Membrane with Deproteinized Bovine Bone Matrix Xenograft. Clinical trial registry of India (CTRI): REF/2023/05/066732. Protocol version: v1 (12/05/23)

Abstract Early diagnosis of Alzheimer’s disease plays a pivotal role in patient care and clinical trials. In this study, we have developed a new approach based on 3D deep convolutional neural networks to accurately differentiate mild Alzheimer’s disease dementia from mild cognitive impairment and cognitively normal individuals using structural MRIs. For comparison, we have built a reference model based on the volumes and thickness of previously reported brain regions that are known to be implicated in disease progression. We validate both models on an internal held-out cohort from The Alzheimer's Disease Neuroimaging Initiative (ADNI) and on an external independent cohort from The National Alzheimer's Coordinating Center (NACC). The deep-learning model is accurate, achieved an area-under-the-curve (AUC) of 85.12 when distinguishing between cognitive normal subjects and subjects with either MCI or mild Alzheimer’s dementia. In the more challenging task of detecting MCI, it achieves an AUC of 62.45. It is also significantly faster than the volume/thickness model in which the volumes and thickness need to be extracted beforehand. The model can also be used to forecast progression: subjects with mild cognitive impairment misclassified as having mild Alzheimer’s disease dementia by the model were faster to progress to dementia over time. An analysis of the features learned by the proposed model shows that it relies on a wide range of regions associated with Alzheimer's disease. These findings suggest that deep neural networks can automatically learn to identify imaging biomarkers that are predictive of Alzheimer's disease, and leverage them to achieve accurate early detection of the disease.