Small Structures Research Articles

Epidemiology and Clinical Characteristics of Cerebral Alveolar Echinococcosis in the Tibetan Region of Sichuan, China.

This study aimed to examine the epidemiology and clinical characteristics of cerebral alveolar echinococcosis in the Tibetan region of Sichuan, China. A retrospective analysis of hospitalized cases of cerebral alveolar echinococcosis from six medical units in the Garze Tibetan Autonomous Prefecture, Sichuan Province, from January 2016 to June 2021 was conducted. The study focused on the characteristics, clinical presentation, and imaging features of the disease. Of 119 cerebral alveolar echinococcosis patients, 76 were male and 43 were female. Occupationally, 62 were farmers, 46 were herdsmen, nine were monks, and two were students. The mean age was 43.9 (± 13.9) years. The primary clinical manifestations were dizziness, headaches, and epilepsy. The incidence of cerebral alveolar echinococcosis was most concentrated within 4 years after the diagnosis of hepatic alveolar echinococcosis (77/119, 64.7%). There were 86 cases (72.3%) with multiple intracranial echinococcosis lesions, with an average size of 2.0 cm × 2.5 cm. The imaging features showed that the lesion was mainly concentrated in the anterior circulation blood supply area, and the lesion had multiple aggregated small vesicular structures as its unique imaging feature. Among 98 follow-up cases, 62 could live independently (63.3%); 18 deaths were recorded (18.4%), with an approximate 5-year survival rate of 81.6%. Regular examination of patients with first diagnosis of hepatic alveolar echinococcosis without a combination of echinococcosis in other parts of the body can help monitor and prevent the occurrence of cerebral alveolar echinococcosis, improve the understanding of cerebral alveolar echinococcosis in Tibetan areas of Sichuan.

Three-dimensional visualization of thyroid ultrasound images based on multi-scale features fusion and hierarchical attention.

Ultrasound three-dimensional visualization, a cutting-edge technology in medical imaging, enhances diagnostic accuracy by providing a more comprehensive and readable portrayal of anatomical structures compared to traditional two-dimensional ultrasound. Crucial to this visualization is the segmentation of multiple targets. However, challenges like noise interference, inaccurate boundaries, and difficulties in segmenting small structures exist in the multi-target segmentation of ultrasound images. This study, using neck ultrasound images, concentrates on researching multi-target segmentation methods for the thyroid and surrounding tissues. We improved the Unet++ to propose PA-Unet++ to enhance the multi-target segmentation accuracy of the thyroid and its surrounding tissues by addressing ultrasound noise interference. This involves integrating multi-scale feature information using a pyramid pooling module to facilitate segmentation of structures of various sizes. Additionally, an attention gate mechanism is applied to each decoding layer to progressively highlight target tissues and suppress the impact of background pixels. Video data obtained from 2D ultrasound thyroid serial scans served as the dataset for this paper.4600 images containing 23,000 annotated regions were divided into training and test sets at a ratio of 9:1, the results showed that: compared with the results of U-net++, the Dice of our model increased from 78.78% to 81.88% (+ 3.10%), the mIOU increased from 73.44% to 80.35% (+ 6.91%), and the PA index increased from 92.95% to 94.79% (+ 1.84%). Accurate segmentation is fundamental for various clinical applications, including disease diagnosis, treatment planning, and monitoring. This study will have a positive impact on the improvement of 3D visualization capabilities and clinical decision-making and research in the context of ultrasound image.

[Clinicopathological and genetic characteristics of common lymphatic malformations in superficial soft tissues].

Objective: To investigate the clinicopathological features, classification, and genetic characteristics of common lymphatic malformation (CLM) in superficial soft tissue. Methods: A retrospective study of 110 patients with the diagnosis of CLM at the Henan Province People's Hospital, China from August 2019 to August 2022 was performed. The clinicopathological features, relevant immunohistochemical (IHC) staining results, and fluorescence quantitative PCR of PIK3CA mutation were analyzed, and patients were followed up. Results: Among the 110 CLM patients, there were 53 males and 57 females; 65 cases (65/110, 59.1%) were first detected when the patients were≤2 years old. The most common location was the head and neck in 41 cases (41/110, 37.3%). Clinically, 102 cases (102/110, 92.7%) were solitary, 83 cases (83/110, 75.5%) were skin-colored, 69 cases (69/110, 62.7%) had indistinct borders, and 10 cases (10/110, 9.1%) had diffuse and severe macroscopic manifestations. There were 52 macrocystic type (52/110, 47.3%), 23 microcystic type (23/110, 20.9%), and 35 combined type (35/110, 31.8%). The macrocystic CLM presented as soft, translucent masses with large cystic cavities on the cut surface, and histologically they were composed of large, irregularly dilated channels that were thicker with irregular smooth muscle and lymphocytic infiltration. Microcystic CLM showed wartlike projections or translucent blisters on the skin, with small honeycomb structures on the cut surface, and histologically consisted of round or angular dilated small lymphatic vessels with little or no smooth muscle. The combined CLM had both macrocystic and microcystic morphologies. IHC staining showed that the lymphatic endothelial cells were positive for LYVE-1, D2-40, PROX1, CD31, and VEGFR3 but negative for CD34; in the macrocystic and combined CLM vessel walls were positive for SMA. Eight of 13 CLM had PIK3CA mutation. All patients were followed up, and 24 (24/110, 21.8%) had relapses, which more frequently occurred in combined type, followed by microcystic type. Conclusions: CLM is a congenital vascular malformation composed of dilated, abnormal lymphatic channels, with PIK3CA mutation. There are significant differences in clinicopathological characteristics among the different types. Since microcystic and combined CLM are prone to recurrence, accurate pathological subtyping is necessary to guide treatment and to predict prognosis.

Endometrial cytological findings for a mesonephric-like endometrial adenocarcinoma: A case report.

A mesonephric-like endometrial adenocarcinoma (ML-EAC) is very rare and has a worse prognosis than other endometrial carcinomas. We describe an ML-EAC and report our endometrial cytological findings. A 76-year-old woman presented with irregular genital bleeding and a uterine mass. Endometrial cytology revealed atypical cylindrical or spindle-shaped cells in the form of small aggregates or solitary cells. The cell aggregates exhibited irregularly stacked papillary structures, small glandular structures, and fenestrated structures. The atypical cells had a nucleus with fine-granular chromatin and a granular cytoplasm, and nuclear grooves and intranuclear pseudo-inclusions were present. Hyaline globules were observed in the glandular lumens and in the background. The presumptive histological type was an adenocarcinoma, but the cytological features were different from those of an endometrioid carcinoma. A histological examination of the endometrial biopsy revealed an adenocarcinoma, and a simple hysterectomy was performed. A grayish-white elevated mass measuring 90 mm × 70 mm × 40 mm was observed on the uterine corpus in the hysterectomy specimen. Histologically, the tumor proliferated as complex tubular structures containing eosinophilic colloid-like materials and trabecular structures. The tumor cells were diffuse and positive for GATA-3 and partially positive for thyroid transcription factor-1. Estrogen and progesterone receptors were negative. An ML-EAC was diagnosed. The tumor was invasive and extended beyond one-half of the muscle layer with a high degree of vascular invasion. In conclusion, we need to focus on the various shapes of the cell aggregate, nuclear grooves, and intranuclear pseudo-inclusions of tumor cells to distinguish an ML-EAC from other endometrial carcinomas in endometrial cytology.

Synergistic optical enhancement of Au/AgNTs@CDs immunoprobe with tips and gaps for SERS/FL dual mode detection of PSA

Robust and highly sensitive nano-optical immunoprobes have emerged as powerful tools to improve the accuracy and sensitivity of early disease diagnosis. This work develops a pentagonal gold/silver nanotube @ carbon dot (Au/AgNTs@CDs) SERS/FL dual-mode immunoprobe for detecting prostate-specific antigen (PSA) in serum by subtly integrating small gaps and branch tip structures. Benefiting from the synergistic optical enhancement of tips and small gaps, this novel rough porous Au/Ag nanotube exhibits larger specific surface area and more active sites as well as remarkable stability. The optical enhancement brought by the innovative structural design increases the detection sensitivity of the immunoprobe to the state of the art. To the best of our knowledge, the limit of detection is an order of magnitude lower than reported in the literature in SERS and fluorescence modes, respectively. Furthermore, both modes exhibit excellent robustness and specificity. Therefore, the design of this immunoprobe provides a new perspective and broad application prospects for improving the sensitivity and accuracy of clinical diagnosis.

The smallest structures in Saturn’s rings from UVIS stellar occultations

On the largest scales Saturn’s rings are often thought of as axisymmetric annuli varying only radially in optical depth with exceptions of spiral waves and eccentric ringlets. But on scales smaller than a few tens of km yet still larger than the largest common ring particles, the assumption of azimuthal symmetry breaks down. Structures such as “straw” in the troughs of density waves, partial gaps around propeller moonlets, and ephemeral particle aggregates such as self-gravity wakes are responsible for the predominant variations in optical depth. During the 13 year Cassini mission, the Ultraviolet Imaging Spectrograph (UVIS) high speed photometer (HSP) measured 80 stellar chord occultations of Saturn’s main rings. In the vicinity of the minimum ring plane radius of each chord, the occultation line-of-sight slewed across the ring plane tangent to the Keplerian motion of the ring particles. These occultations measured ultraviolet light in the wavelength range 110–190 nm with 1- or 2-ms ms integration times, providing optical depth measurements with resolution comparable to the Fresnel scale of ∼10 m in the frame co-moving with the local Keplerian speed. These high-resolution chord occultations reach their minimum ring radii over a broad range of radial locations within Saturn’s main rings and resolve non-axisymmetric structures in a wide variety of ring regions. We measure the azimuthal length scales and optical depth profiles of “ghosts”, or azimuthally limited gaps with radial scales less than 30 m (Baillié et al., 2013), in the C ring plateaus. We measure the length scale of transparent gaps and self-gravity wakes in the peaks and troughs of spiral density waves. We present optical depth profiles which resolve axisymmetric waves in the A and B rings and constrain the azimuthal length scale over which the waves remain axisymmetric to ∼ 1000 km. We combine autocorrelation length scales from stellar occultations which cut across the minimum ring radius of a chord occultation with line-of-sight trajectories from other occultations which are not tangent to the rings to constrain the morphology of the azimuthally and temporally averaged mesoscale structures at that ring radius. 2D autocorrelation profiles from stellar occultations show self-gravity wakes and axisymmetric waves often coexisting.

Iron projectile fractionation processes in siliceous glass from small impact craters

Detection of extra-terrestrial geochemical components in melt generated during meteorite impact provides diagnostic evidence that can be used to confirm a hypervelocity impact event, and in some cases, classify the projectile. However, projectile contamination is often present at sub-percent levels, and can be difficult to detect. In contrast, meteoritic abundances in glass from small impact craters (<1 km diameter) formed by iron meteorites can be anomalously high, which has been attributed to glass originating from the projectile-target interface. Emulsion textures, immiscible liquids, metal spherules, and non-meteoritic siderophile element ratios have been cited as evidence that the projectile component is typically fractionated in impact glass. Here we present compositional data for impact glass from the Henbury crater field in Australia, where the largest crater is 145 m in diameter and the subgreywacke target rock and IIIAB iron projectile are geochemically distinct. Mixing models (Fe-Si, Ni-Co, Cr-Ir) and high platinum group element abundances indicate average projectile contributions ranging from 3 to 13 % in Henbury glass, comparable to ranges reported in glass from the Kamil (Egypt) and Wabar (Saudi Arabia) impact craters. However meteoritic siderophile element ratios (Fe:Ni, Fe:Co, Ni:Co) in Henbury glass appear nearly unfractionated, whereas Wabar and Kamil glasses have more fractionated ratios. Observed variations are attributed to fractionation of meteoritic Ni by formation of immiscible Ni-rich spherules during oxidation of meteoritic iron, and subsequent separation of Ni-rich spherules from glass during ejection. The Henbury glass sample analyzed is interpreted as an example of an interface melt that quenched prior to extensive oxidation and phase separation, and thus may represent one of the least fractionated samples of melt from the projectile-target interface described thus far, whereas Wabar and Kamil glasses record more evidence of fractionation processes. These results further highlight the influence of metal spherule formation on the composition of ejected glass from small impact structures formed by iron meteorites and provide new insights that explain textural features observed in natural impact glasses.

Viral PIC-pocketing: RSV sequestration of translational preinitiation complexes into bi-phasic biomolecular condensates.

Respiratory syncytial viruses (RSVs) of cows and humans are a significant cause of morbidity and mortality in their respective populations. These RNA viruses replicate in the infected cells by compartmentalizing the cell's cytoplasm into distinct viral microdomains called inclusion bodies (IBs). In this paper, we show that these IBs are further compartmentalized into smaller structures that have significantly different density, as observed by electron microscopy. Within smaller intra-IB structures, we observed ribosomal components and evidence for active translation. These findings highlight that RSV may additionally compartmentalize translation to favor its own replication in the cell. These data contribute to our understanding of how RNA viruses hijack the cell to favor replication of their own genomes and may provide new targets for antiviral therapeutics in vivo.

A gelatin-zirconium phosphate nanoparticles composite interlayer for enhancing compaction resistance and antifouling performance of TFC NF membrane

From a practical point of view, the thin-film composite (TFC) nanofiltration (NF) membrane should not only have superior separation performance but also excellent compaction resistance and antifouling properties. Generally, polyamide (PA) separation layers of the TFC NF membrane prepared on the support with hydrophilic interlayer are crumpled, which may be detrimental to the compaction resistance and antifouling properties of TFC NF membranes. A flexible polymer-rigid nanoparticles composite interlayer was constructed on the pristine polysulfone (PSF) support in this work to design a TFC NF membrane with compaction resistance, antifouling, and excellent separation performance. Morphology and crosslinking degree of PA separation layers were investigated by scanning electron microscopy (SEM), atomic force microscope (AFM), and X-ray photoelectron spectroscopy (XPS). The results demonstrated that the composite interlayer can not only regulate the distribution and diffusion of piperazine (PIP) but also act as a template to induce the generation and growth of PA during the interfacial polymerization (IP) process, leading to the formation of the PA separation layer with a small nodular structure. The compaction resistance, antifouling properties, and separation performance of the TFC membrane were also investigated by nanoindentation, fouling experiment, and filtration test, respectively. The TFC NF membrane with the composite interlayer showed greatly improved mechanical properties with its hardness and elastic modulus approximately 1.5 and 1.6 times that of the reference, respectively. Furthermore, the flux recovery of the TFC NF membrane with the composite interlayer (93.8 %) was higher than that of the control (87.2 %), indicating that the TFC NF membrane with the composite interlayer had better antifouling properties. In addition, the obtained TFC NF membrane with the composite interlayer showed a water flux approximately twice as high as that of the reference with satisfactory rejection. This advancement will contribute to the development of more efficient and stable TFC NF membranes for industrial wastewater treatment.

The method and implementation of a Taiwan building recognition model based on YOLOX-S and illustration enhancement

Earthquakes pose significant risks in Taiwan, necessitating effective risk assessment and preventive measures to reduce damage. Obtaining complete building structure data is crucial for the accurate evaluation of earthquake-induced losses. However, manual annotation of building structures is time-consuming and inefficient, resulting in incomplete data. To address this, we propose YOLOX-CS, an object detection model, combined with the Convolutional Block Attention Module (CBAM), to enhance recognition capabilities for small structures and reduce background interference. Additionally, we introduce the Illustration Enhancement data augmentation method to improve the recognition of obscured buildings. We collected diverse building images and manually annotated them, resulting in a dataset for training the model. YOLOX-CS with CBAM significantly improves recognition accuracy, particularly for small objects, and Illustration Enhancement enhances the recognition of occluded buildings. Our proposed approach advances building structure recognition, contributing to more effective earthquake risk assessment systems in Taiwan and beyond.

Leukemogenesis occurs in a microenvironment enriched by extracellular microvesicles/exosomes: recent discoveries and questions to be answered.

In single-cell organisms, extracellular microvesicles (ExMVs) were one of the first cell-cell communication platforms that emerged very early during evolution. Multicellular organisms subsequently adapted this mechanism. Evidence indicates that all types of cells secrete these small circular structures surrounded by a lipid membrane that may be encrusted by ligands and receptors interacting with target cells and harboring inside a cargo comprising RNA species, proteins, bioactive lipids, signaling nucleotides, and even entire organelles "hijacked" from the cells of origin. ExMVs are secreted by normal cells and at higher levels by malignant cells, and there are some differences in their cargo. On the one hand, ExMVs secreted from malignant cells interact with cells in the microenvironment, and in return, they are exposed by a "two-way mechanism" to ExMVs secreted by non-leukemic cells. Therefore, leukemogenesis occurs and progresses in ExMVs enriched microenvironments, and this biological fact has pathologic, diagnostic, and therapeutic implications. We are still trying to decipher this intriguing cell-cell communication language better. We will present a current point of view on this topic and review some selected most recent discoveries and papers.

Improved reconstruction for highly accelerated propeller diffusion 1.5T clinical MRI.

Propeller fast-spin-echo diffusion magnetic resonance imaging (FSE-dMRI) is essential for the diagnosis of Cholesteatoma. However, at clinical 1.5T MRI, its signal-to-noise ratio (SNR) remains relatively low. To gain sufficient SNR, signal averaging (number of excitations, NEX) is usually used with the cost of prolonged scan time. In this work, we leveraged the benefits of Locally Low Rank (LLR) constrained reconstruction to enhance the SNR. Furthermore, we enhanced both the speed and SNR by employing Convolutional Neural Networks (CNNs) for the accelerated PROPELLER FSE-dMRI on a 1.5T clinical scanner. Residual U-Net (RU-Net) was found to be efficient for propeller FSE-dMRI data. It was trained to predict 2-NEX images obtained by Locally Low Rank (LLR) constrained reconstruction and used 1-NEX images obtained via simplified reconstruction as the inputs. The brain scans from healthy volunteers and patients with cholesteatoma were performed for model training and testing. The performance of trained networks was evaluated with normalized root-mean-square-error (NRMSE), structural similarity index measure (SSIM), and peak SNR (PSNR). For 4 × under-sampled with 7 blades data, online reconstruction appears to provide suboptimal images-some small details are missing due to high noise interferences. Offline LLR enables suppression of noises and discovering some small structures. RU-Net demonstrated further improvement compared to LLR by increasing 18.87% of PSNR, 2.11% of SSIM, and reducing 53.84% of NRMSE. Moreover, RU-Net is about 1500 × faster than LLR (0.03 vs. 47.59s/slice). The LLR remarkably enhances the SNR compared to online reconstruction. Moreover, RU-Net improves propeller FSE-dMRI as reflected in PSNR, SSIM, and NRMSE. It requires only 1-NEX data, which allows a 2 × scan time reduction. In addition, its speed is approximately 1500 times faster than that of LLR-constrained reconstruction.

Utilizing Extracellular Vesicles for Eliminating 'Unwanted Molecules': Harnessing Nature's Structures in Modern Therapeutic Strategies.

Extracellular vesicles (EVs) are small phospholipid bilayer-bond structures released by diverse cell types into the extracellular environment, maintaining homeostasis of the cell by balancing cellular stress. This article provides a comprehensive overview of extracellular vesicles, their heterogeneity, and diversified roles in cellular processes, emphasizing their importance in the elimination of unwanted molecules. They play a role in regulating oxidative stress, particularly by discarding oxidized toxic molecules. Furthermore, endoplasmic reticulum stress induces the release of EVs, contributing to distinct results, including autophagy or ER stress transmission to following cells. ER stress-induced autophagy is a part of unfolded protein response (UPR) and protects cells from ER stress-related apoptosis. Mitochondrial-derived vesicles (MDVs) also play a role in maintaining homeostasis, as they carry damaged mitochondrial components, thereby preventing inflammation. Moreover, EVs partake in regulating aging-related processes, and therefore they can potentially play a crucial role in anti-aging therapies, including the treatment of age-related diseases such as Alzheimer's disease or cardiovascular conditions. Overall, the purpose of this article is to provide a better understanding of EVs as significant mediators in both physiological and pathological processes, and to shed light on their potential for therapeutic interventions targeting EV-mediated pathways in various pathological conditions, with an emphasis on age-related diseases.

Microvascular damage, neuroinflammation and extracellular matrix remodeling in Col18a1 knockout mice as a model for early cerebral small vessel disease

Collagen type XVIII (COL18) is an abundant heparan sulfate proteoglycan in vascular basement membranes. Here, we asked (i) if the loss of COL18 would result in blood-brain barrier (BBB) breakdown, pathological alterations of small arteries and capillaries and neuroinflammation as found in cerebral small vessel disease (CSVD) and (ii) if such changes may be associated with remodeling of synapses and neural extracellular matrix (ECM). We found that 5-month-old Col18a1−/− mice had elevated BBB permeability for mouse IgG in the deep gray matter, and intravascular erythrocyte accumulations were observed brain-wide in capillaries and arterioles. BBB permeability increased with age and affected cortical regions and the hippocampus in 12-month-old Col18a1−/− mice. None of the Col18a1−/− mice displayed hallmarks of advanced CSVD, such as hemorrhages, and did not show perivascular space enlargement. Col18a1 deficiency-induced BBB leakage was accompanied by activation of microglia and astrocytes, a loss of aggrecan in the ECM of perineuronal nets associated with fast-spiking inhibitory interneurons and accumulation of the perisynaptic ECM proteoglycan brevican and the microglial complement protein C1q at excitatory synapses. As the pathway underlying these regulations, we found increased signaling through the TGF-ß1/Smad3/TIMP-3 cascade. We verified the pivotal role of COL18 for small vessel wall structure in CSVD by demonstrating the protein's involvement in vascular remodeling in autopsy brains from patients with cerebral hypertensive arteriopathy. Our study highlights an association between the alterations of perivascular ECM, extracellular proteolysis, and perineuronal/perisynaptic ECM, as a possible substrate of synaptic and cognitive alterations in CSVD.

Spectrum learning for super-resolution tomographic reconstruction.

Objective. Computed Tomography (CT) has been widely used in industrial high-resolution non-destructive testing. However, it is difficult to obtain high-resolution images for large-scale objects due to their physical limitations. The objective is to develop an improved super-resolution technique that preserves small structures and details while efficiently capturing high-frequency information.Approach. The study proposes a new deep learning based method called spectrum learning (SPEAR) network for CT images super-resolution. This approach leverages both global information in the image domain and high-frequency information in the frequency domain. The SPEAR network is designed to reconstruct high-resolution images from low-resolution inputs by considering not only the main body of the images but also the small structures and other details. The symmetric property of the spectrum is exploited to reduce weight parameters in the frequency domain. Additionally, a spectrum loss is introduced to enforce the preservation of both high-frequency components and global information.Main results. The network is trained using pairs of low-resolution and high-resolution CT images, and it is fine-tuned using additional low-dose and normal-dose CT image pairs. The experimental results demonstrate that the proposed SPEAR network outperforms state-of-the-art networks in terms of image reconstruction quality. The approach successfully preserves high-frequency information and small structures, leading to better results compared to existing methods. The network's ability to generate high-resolution images from low-resolution inputs, even in cases of low-dose CT images, showcases its effectiveness in maintaining image quality.Significance. The proposed SPEAR network's ability to simultaneously capture global information and high-frequency details addresses the limitations of existing methods, resulting in more accurate and informative image reconstructions. This advancement can have substantial implications for various industries and medical diagnoses relying on accurate imaging.

A geostatistical analysis of multiscale metallicity variations in galaxies – III. Spatial resolution and data quality limits

ABSTRACT Geostatistical methods are powerful tools for understanding the spatial structure of the metallicity distribution of galaxies, and enable construction of accurate predictive models of the 2D metallicity distribution. However, so far these methods have only been applied to very high spatial resolution metallicity maps, leaving it uncertain if they will work on lower quality data. In this study, we apply geostatistical techniques to high-resolution spectroscopic maps of three local galaxies convolved to eight different spatial resolutions ranging from ∼40 pc to ∼1 kpc per pixel. We fit a geostatistical model to the data at all resolutions, and find that for metallicity maps where small-scale structure is visible by eye (with ≳10 resolution elements per Re), all parameters, including the metallicity correlation scale, can be recovered accurately. At all resolutions tested, we find that point metallicity predictions from such a geostatistical model outperform a circularly symmetric metallicity gradient model. We also explore dependence on the number of data points, and find that N ≳ 100 spatially resolved metallicity values are sufficient to train a geostatistical model that yields more accurate metallicity predictions than a radial gradient model. Finally, we investigate the potential detrimental effects of having spaxels smaller than an individual H ii region by repeating our analysis with metallicities integrated over H ii regions. We see that spaxel-based measurements have more noise, as expected, but the underlying spatial metallicity distribution can be recovered regardless of whether spaxels or integrated regions are used.

Hydrogeological Characteristics of the Makaresh Carbonate Karst Massif (Central Albania)

Carbonate rocks cover about 23% of Albania, with exploitable karst water resources estimated at 2.84 × 109 m3/year (about 65% of the total exploitable groundwater resources in the country). The Kruja tectonic zone is characterized by the presence of SE–NW-oriented carbonate structures, rich in fresh and thermal groundwaters. More than 80% of the thermal springs in Albania are present in this tectonic zone. One of its most interesting carbonate structures, with the presence of both cold and thermal waters, is the small karst structure of Makaresh, with a surface of 22 km2. The purpose of this article is to describe the hydrogeological characteristics of this massif; based on the physico-chemical characteristics, groundwaters of the study area are classified as cold waters (belonging to the local flow system) and thermal waters (originating in intermediate/deep flow systems). The former are mainly of HCO3-Ca or HCO3-Ca-Mg type (electrical conductivity 580–650 μS/cm, Temperature 13.9–16.6 °C). Thermal waters are mainly of the Cl-Na-Ca type (EC 7200–7800 μS/cm, T 18.5–22.5 °C); they are further characterized by high hydrogen sulfide concentration, up to about 350 mg/L. The presence of two groundwater types in the Makaresh massif is connected to the presence of two groundwater circulation systems. The main factors of the groundwater physico-chemical quality are the dissolution of rocks and minerals contained therein, the presence of hypogenic speleogenesis, and the mixing of the groundwater of the two systems. The hydrogeological studies proved that karst rocks contain considerable freshwater resources, partly used for water supply. Thermal waters are not currently exploited due to their temperature, but they are potentially suitable for thermal uses by drilling boreholes to a depth of about 1000 m.

Evolution of the Microrobots: Stimuli-Responsive Materials and Additive Manufacturing Technologies Turn Small Structures into Microscale Robots.

The development of functional microsystems and microrobots that have characterized the last decade is the result of a synergistic and effective interaction between the progress of fabrication techniques and the increased availability of smart and responsive materials to be employed in the latter. Functional structures on the microscale have been relevant for a vast plethora of technologies that find application in different sectors including automotive, sensing devices, and consumer electronics, but are now also entering medical clinics. Working on or inside the human body requires increasing complexity and functionality on an ever-smaller scale, which is becoming possible as a result of emerging technology and smart materials over the past decades. In recent years, additive manufacturing has risen to the forefront of this evolution as the most prominent method to fabricate complex 3D structures. In this review, we discuss the rapid 3D manufacturing techniques that have emerged and how they have enabled a great leap in microrobotic applications. The arrival of smart materials with inherent functionalities has propelled microrobots to great complexity and complex applications. We focus on which materials are important for actuation and what the possibilities are for supplying the required energy. Furthermore, we provide an updated view of a new generation of microrobots in terms of both materials and fabrication technology. While two-photon lithography may be the state-of-the-art technology at the moment, in terms of resolution and design freedom, new methods such as two-step are on the horizon. In the more distant future, innovations like molecular motors could make microscale robots redundant and bring about nanofabrication.

The ssgB gene is required for the early stages of sporangium formation in Actinoplanes missouriensis.

SsgB has been proposed as an archetypical SsgA-like protein with an evolutionarily conserved function in the morphological development of spore-forming actinomycetes. SsgB in Streptomyces coelicolor A3(2) is involved in spore septum formation. However, it is unclear whether this is the primary function of SsgBs in actinobacteria. This study demonstrated that the SsgB ortholog (AmSsgB) in Actinoplanes missouriensis is essential for sporangium expansion, which does not seem to be related to spore septum formation. However, the heterologous expression of ssgB from S. coelicolor A3(2) restored morphological abnormalities in the ΔAmssgB mutant. We propose that the primary function of SsgB is to initiate sporulation in differentiating cells (e.g., aerial hyphae in Streptomyces and "presporangium" cells in A. missouriensis) although its molecular mechanism remains unknown.

Multi-component Dark Matter and small scale structure formation

We consider the evolution of non-thermal dark matter perturbations in models which contain both Weakly Interacting Massive Particles (WIMPs) and axions. Using constraints from existing observations we examine the percentage of WIMPs and axions that may comprise the cosmological dark matter budget in models with an Early Matter Dominated Epoch (EMDE) — where entropy production is important. After carefully tracking the thermal evolution of the various species by solving the Boltzmann equations, we consider the enhancement of perturbations that may have led to early structure formation for axions and WIMPs. We investigate the impact of enhanced perturbations on the parameter space of both species, after imposing existing constraints from indirect detection experiments. Given these constraints we establish the feasibility of axions to form miniclusters in the early universe in EMDEs for a given percentage of allowed WIMPs. We find that EMDEs with low reheat temperatures near the BBN limit are preferred for axion minicluster formation. When the EMDE is caused by string moduli, the WIMP contribution to the relic density is set by the moduli branching to dark matter at the level of ≲ O\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ \\mathcal{O} $$\\end{document}(10−4).