Melanoma biology and treatment: a review of novel regulated cell death-based approaches.

The incidence of melanoma, the most lethal form of skin cancer, has increased due to ultraviolet exposure. The treatment of advanced melanoma, particularly metastatic cases, remains challenging with poor outcomes. Targeted therapies involving BRAF/MEK inhibitors and immunotherapy based on anti-PD1/anti-CTLA4 antibodies have achieved long-term survival rates of approximately 50% for patients with advanced melanoma. However, therapy resistance and inadequate treatment response continue to hinder further breakthroughs in treatments that increase survival rates. This review provides an introduction to the molecular-level pathogenesis of melanoma and offers an overview of current treatment options and their limitations. Cells can die by either accidental or regulated cell death (RCD). RCD is an orderly cell death controlled by a variety of macromolecules to maintain the stability of the internal environment. Since the uncontrolled proliferation of tumor cells requires evasion of RCD programs, inducing the RCD of melanoma cells may be a treatment strategy. This review summarizes studies on various types of nonapoptotic RCDs, such as autophagy-dependent cell death, necroptosis, ferroptosis, pyroptosis, and the recently discovered cuproptosis, in the context of melanoma. The relationships between these RCDs and melanoma are examined, and the interplay between these RCDs and immunotherapy or targeted therapy in patients with melanoma is discussed. Given the findings demonstrating melanoma cell death in response to different stimuli associated with these RCDs, the induction of RCD shows promise as an integral component of treatment strategies for melanoma.

Nutritional deficiencies in alcohol use disorder/alcohol-associated liver disease.

PURPOSE OF REVIEW: To delineate common and uncommon dietary and nutritional deficiencies in individuals with chronic heavy alcohol use and alcohol use disorder and to highlight important advances in the nutrition field in patients ranging from those with alcohol use disorder (AUD) and no liver disease to those with decompensated alcohol-associated liver disease (ALD). RECENT FINDINGS: Patients with AUD may have nutritional deficiencies, especially isolated nutrient deficiencies, such as thiamine or zinc deficiencies. This should not be surprising, as alcohol is a major source of "empty calories." It is devoid of critical macronutrients, such as protein, and micronutrients including important vitamins and minerals. Patients with AUD frequently drink much more than often appreciated (10-20 drinks a day). Patients with AUD and early ALD often begin to develop more apparent nutritional deficiencies. Healthcare providers need to be aware of the presenting features of individual nutrient deficiencies, such as thiamine deficiency, and to provide prompt treatment. In patients with more advanced liver disease, malnutrition correlates with severity of liver disease. It is important to understand the value of nutritional support throughout the spectrum of AUD. SUMMARY: We review nutritional deficiencies in the spectrum of patients with AUD and ALD and highlight new information and recommendations.

Machine learning enables detection of early-stage colorectal cancer by whole-genome sequencing of plasma cell-free DNA.

BACKGROUND: Blood-based methods using cell-free DNA (cfDNA) are under development as an alternative to existing screening tests. However, early-stage detection of cancer using tumor-derived cfDNA has proven challenging because of the small proportion of cfDNA derived from tumor tissue in early-stage disease. A machine learning approach to discover signatures in cfDNA, potentially reflective of both tumor and non-tumor contributions, may represent a promising direction for the early detection of cancer. METHODS: Whole-genome sequencing was performed on cfDNA extracted from plasma samples (N = 546 colorectal cancer and 271 non-cancer controls). Reads aligning to protein-coding gene bodies were extracted, and read counts were normalized. cfDNA tumor fraction was estimated using IchorCNA. Machine learning models were trained using k-fold cross-validation and confounder-based cross-validations to assess generalization performance. RESULTS: In a colorectal cancer cohort heavily weighted towards early-stage cancer (80% stage I/II), we achieved a mean AUC of 0.92 (95% CI 0.91-0.93) with a mean sensitivity of 85% (95% CI 83-86%) at 85% specificity. Sensitivity generally increased with tumor stage and increasing tumor fraction. Stratification by age, sequencing batch, and institution demonstrated the impact of these confounders and provided a more accurate assessment of generalization performance. CONCLUSIONS: A machine learning approach using cfDNA achieved high sensitivity and specificity in a large, predominantly early-stage, colorectal cancer cohort. The possibility of systematic technical and institution-specific biases warrants similar confounder analyses in other studies. Prospective validation of this machine learning method and evaluation of a multi-analyte approach are underway.

Riches of phenotype computationally extracted from microbial colonies.

The genetic, epigenetic, and physiological differences among cells in clonal microbial colonies are underexplored opportunities for discovery. A recently developed genetic assay reveals that transient losses of heterochromatic repression, a heritable form of gene silencing, occur throughout the growth of Saccharomyces colonies. This assay requires analyzing two-color fluorescence patterns in yeast colonies, which is qualitatively appealing but quantitatively challenging. In this paper, we developed a suite of automated image processing, visualization, and classification algorithms (MORPHE) that facilitated the analysis of heterochromatin dynamics in the context of colonial growth and that can be broadly adapted to many colony-based assays in Saccharomyces and other microbes. Using the features that were automatically extracted from fluorescence images, our classification method distinguished loss-of-silencing patterns between mutants and wild type with unprecedented precision. Application of MORPHE revealed subtle but significant differences in the stability of heterochromatic repression between various environmental conditions, revealed that haploid cells experienced higher rates of silencing loss than diploids, and uncovered the unexpected contribution of a sirtuin to heterochromatin dynamics.

Prediction of ribosome footprint profile shapes from transcript sequences.

MOTIVATION: Ribosome profiling is a useful technique for studying translational dynamics and quantifying protein synthesis. Applications of this technique have shown that ribosomes are not uniformly distributed along mRNA transcripts. Understanding how each transcript-specific distribution arises is important for unraveling the translation mechanism. RESULTS: Here, we apply kernel smoothing to construct predictive features and build a sparse model to predict the shape of ribosome footprint profiles from transcript sequences alone. Our results on Saccharomyces cerevisiae data show that the marginal ribosome densities can be predicted with high accuracy. The proposed novel method has a wide range of applications, including inferring isoform-specific ribosome footprints, designing transcripts with fast translation speeds and discovering unknown modulation during translation. AVAILABILITY AND IMPLEMENTATION: A software package called riboShape is freely available at https://sourceforge.net/projects/riboshape CONTACT: yss@berkeley.edu.

An individualized predictor of health and disease using paired reference and target samples.

BACKGROUND: Consider the problem of designing a panel of complex biomarkers to predict a patient's health or disease state when one can pair his or her current test sample, called a target sample, with the patient's previously acquired healthy sample, called a reference sample. As contrasted to a population averaged reference this reference sample is individualized. Automated predictor algorithms that compare and contrast the paired samples to each other could result in a new generation of test panels that compare to a person's healthy reference to enhance predictive accuracy. This paper develops such an individualized predictor and illustrates the added value of including the healthy reference for design of predictive gene expression panels. RESULTS: The objective is to predict each subject's state of infection, e.g., neither exposed nor infected, exposed but not infected, pre-acute phase of infection, acute phase of infection, post-acute phase of infection. Using gene microarray data collected in a large scale serially sampled respiratory virus challenge study we quantify the diagnostic advantage of pairing a person's baseline reference with his or her target sample. The full study consists of 2886 microarray chips assaying 12,023 genes of 151 human volunteer subjects under 4 different inoculation regimes (HRV, RSV, H1N1, H3N2). We train (with cross-validation) reference-aided sparse multi-class classifier algorithms on this data to show that inclusion of a subject's reference sample can improve prediction accuracy by as much as 14 %, for the H3N2 cohort, and by at least 6 %, for the H1N1 cohort. Remarkably, these gains in accuracy are achieved by using smaller panels of genes, e.g., 39 % fewer for H3N2 and 31 % fewer for H1N1. The biomarkers selected by the predictors fall into two categories: 1) contrasting genes that tend to differentially express between target and reference samples over the population; 2) reinforcement genes that remain constant over the two samples, which function as housekeeping normalization genes. Many of these genes are common to all 4 viruses and their roles in the predictor elucidate the function that they play in differentiating the different states of host immune response. CONCLUSIONS: If one uses a suitable mathematical prediction algorithm, inclusion of a healthy reference in biomarker diagnostic testing can potentially improve accuracy of disease prediction with fewer biomarkers.

Multiantigenic peptide-polymer conjugates as therapeutic vaccines against cervical cancer.

Immunotherapy is one of the most promising strategies for the treatment of cancer. Human papillomavirus (HPV) is responsible for virtually all cases of cervical cancer. The main purpose of a therapeutic HPV vaccine is to stimulate CD8(+) cytotoxic T lymphocytes (CTLs) that can eradicate HPV infected cells. HPV oncoproteins E6 and E7 are continuously expressed and are essential for maintaining the growth of HPV-associated tumor cells. We designed polymer-based multi-antigenic formulations/constructs that were comprised of the E6 and E7 peptide epitopes. We developed an N-terminus-based epitope conjugation to conjugate two unprotected peptides to poly tert-butyl acrylate. This method allowed for the incorporation of the two antigens into a polymeric dendrimer in a strictly equimolar ratio. The most effective formulations eliminated tumors in up to 50% of treated mice. Tumor recurrence was not observed up to 3months post initial challenge.

Combined synthetic and recombinant techniques for the development of lipoprotein-based, self-adjuvanting vaccines targeting human papillomavirus type-16 associated tumors.

Human papillomaviruses (HPVs) are associated with various cancers, with HPV16 linked to more than half of cervical cancer cases. Vaccines to prevent HPV infection and cancer development have proven effective, but are not useful in individuals with prior HPV exposure. Treatment vaccines to eradicate or control HPV-associated lesions are therefore desirable for these patients. Herein we describe the development of a process to enable the production of semisynthetic vaccines based on the site-specific attachment of synthetic bacterial lipid analogs (e.g., Pam2Cys) to a non-oncogenic mutant HPV16 E7 protein to generate molecularly defined vaccines. Many cytotoxic lymphocyte (CTL) epitopes from E7 are delivered by this approach; potentially ensuring that large numbers of immunized individuals can generate CTLs to clear HPV infected cells. Delivery of this construct reduced the growth of HPV16-associated tumors in a TC1 mouse model, the effects of which were better than the potent CTL epitope HPV16 E7(44-57) administered with Montanide ISA51 adjuvant.

Efficient Compressive Strength Prediction of Alkali-Activated Waste Materials Using Machine Learning.

This study explores the integration of machine learning (ML) techniques to predict and optimize the compressive strength of alkali-activated materials (AAMs) sourced from four industrial waste streams: blast furnace slag, fly ash, reducing slag, and waste glass. Aimed at mitigating the labor-intensive trial-and-error method in AAM formulation, ML models can predict the compressive strength and then streamline the mixture compositions. By leveraging a dataset of only 42 samples, the Random Forest (RF) model underwent fivefold cross-validation to ensure reliability. Despite challenges posed by the limited datasets, meticulous data processing steps facilitated the identification of pivotal features that influence compressive strength. Substantial enhancement in predicting compressive strength was achieved with the RF model, improving the model accuracy from 0.05 to 0.62. Experimental validation further confirmed the ML model's efficacy, as the formulations ultimately achieved the desired strength threshold, with a significant 59.65% improvement over the initial experiments. Additionally, the fact that the recommended formulations using ML methods only required about 5 min underscores the transformative potential of ML in reshaping AAM design paradigms and expediting the development process.

Element Screening Engineering for High-Entropy Alloy Anodes: Achieving Fast and Robust Li-Storage With Optimal Working Potential.

While the high-entropy strategy is highly effective in enhancing the performance of materials across various fields, an optimal methodology for selecting component elements for performance optimization is still lacking. Here the findings on uncovering the element selection rules for rational design of high-entropy alloy anodes with exceptional lithium storage performance are reported. It is investigated high-entropy element screening rules by modifying stable diamond-structured Ge with P to induce a tetrahedrally coordinated sphalerite structure for enhanced metallic conductivity, further stabilized by incorporating Zn and other elements. Moreover, both theoretical and experimental results confirm that Li-storage performance improves with increasing atomic number: BZnGeP3 < AlZnGeP3 < GaZnGeP3 < InZnGeP3. InZnGeP3-based electrodes demonstrate the highest Li-ion affinity, fastest electronic and Li-ion transport, largest Li-storage capacity and reversibility, and best mechanical integrity. Further element screening based on the above criteria leads to high entropy alloy anodes with metallic conductivity like GaCuSnInZnGeP6, GaCu(or Sn)InZnGeP5, CuSnInZnGeP5, InZnGePSeS(or Te), InZnGeP2S(or Se) which show superior Li-storage performances. The excellent phase stability is attributed to their high configurational entropy. This study offers profound insights into element screening for high-entropy alloy-based anodes in Li-ion batteries, providing guidance and reference for the element combination and screening of other high-entropy functional materials.

Verbal training can improve neurocognitive and reading performance by increasing white matter integrity and grey matter volume.

INTRODUCTION: Dementia and mild cognitive impairment (MCI) present both health and economic challenges on a global scale, thus affecting millions of people, and is projected to increase significantly by the year 2050. Early language processing deficits are evident in those diagnosed with Alzheimer's disease and MCI. Recent advances in pharmacologic and non-pharmacologic interventions, including cognitive rehabilitation and training, show promising effects on cognitive functions. Articulation training, particularly, is highlighted for its potential in addressing the communication difficulties which those experiencing dementia and MCI face, based on the transmission deficit hypothesis. This study aimed to perform a voxel-wise comparison of morphological changes in grey matter volume as well as white matter integrity to represent the plastic changes in response to articulation training among older, healthy Japanese adults. METHODS: Forty older, healthy Japanese adults were randomized into either a cognitive training group or a control group. The study involved comprehensive behavioral assessments, neuroimaging (including 3D anatomy, fMRI and Diffusion Tensor Imaging), and a structured verbal articulation training regimen. The training included reading tasks which focused on enhancing both articulation and phonological skills. Neuroimaging data were acquired using a 3 Tesla Siemens MR scanner, with the FSL tool being used for white matter analysis and the CAT12 toolbox for grey matter analysis. RESULTS: Significant increases in grey matter volume were observed in certain regions, including the left Supplementary motor area, Postcentral gyrus, and bilateral Superior frontal gyrus among those in the training group. Correlations were noted between reading abilities and cortical volume in areas such as the left Middle temporal gyrus, pulvinar, and Middle occipital gyrus. White matter integrity also improved, as evidenced by increased fractional anisotropy in tracts such as the superior longitudinal fasciculus, corona radiata, and internal capsule. These findings suggest a link between articulation training and enhanced neuroplasticity in both grey and white matter regions related to language processing. CONCLUSION: The study demonstrates that a 4-week verbal articulation training intervention period can lead to significant improvements in grey matter volume in the left Supplementary motor area, the left Postcentral gyrus, and the bilateral Superior frontal gyrus, as well as the integrity of white matter tracts associated with language processing among older adults. These results suggest that such training could be a valuable tool in enhancing cognitive functions related to language in older populations.

Conserved regulatory switches for the transition from natal down to juvenile feather in birds.

The transition from natal downs for heat conservation to juvenile feathers for simple flight is a remarkable environmental adaptation process in avian evolution. However, the underlying epigenetic mechanism for this primary feather transition is mostly unknown. Here we conducted time-ordered gene co-expression network construction, epigenetic analysis, and functional perturbations in developing feather follicles to elucidate four downy-juvenile feather transition events. We report that extracellular matrix reorganization leads to peripheral pulp formation, which mediates epithelial-mesenchymal interactions for branching morphogenesis. α-SMA (ACTA2) compartmentalizes dermal papilla stem cells for feather renewal cycling. LEF1 works as a key hub of Wnt signaling to build rachis and converts radial downy to bilateral symmetry. Novel usage of scale keratins strengthens feather sheath with SOX14 as the epigenetic regulator. We show that this primary feather transition is largely conserved in chicken (precocial) and zebra finch (altricial) and discuss the possibility that this evolutionary adaptation process started in feathered dinosaurs.

Self-adjuvanting polymer-peptide conjugates as therapeutic vaccine candidates against cervical cancer.

Dendrimers are structurally well-defined, synthetic polymers with sizes and physicochemical properties often resembling those of biomacromolecules (e.g., proteins). As a result, they are promising candidates for peptide-based vaccine delivery platforms. Herein, we established a synthetic pathway to conjugate a human papillomavirus (HPV) E7 protein-derived peptide antigen to a star-polymer to create a macromolecular vaccine candidate to treat HPV-related cancers. These conjugates were able to reduce tumor growth and eradicate E7-expressing TC-1 tumors in mice after a single immunization, without the help of any external adjuvant.

Microwave-assisted synthesis of difficult sequence-containing peptides using the isopeptide method.

Microwave-assisted Fmoc solid phase peptide synthesis (SPPS) was applied in combination with the isopeptide strategy to establish a new method for the rapid synthesis of difficult sequence-containing peptide. A model peptide (8Q(Ser)) was produced in one day using the method developed, in contrast with two weeks using the isopeptide method. Both methods produced the desired peptide in high yield and purity, while classical SPPS did not result in the desired product.

Congenital staphylococcal scalded skin syndrome in a preterm infant.

Staphylococcal scalded skin syndrome (SSSS) is a rare condition in premature infants. We report a case of SSSS in a preterm neonate who displayed all clinical manifestations at birth, leading to a fatal outcome from Candida parapsilosis fungemia. The clinical presentation was challenging to differential diagnosis. SSSS diagnosis was confirmed by skin biopsy. This case emphasizes the significance of early recognition and diagnosis of SSSS promptly for clinicians. Congenital SSSS in premature infants can be fatal, but with early recognition and appropriate supportive and antimicrobial therapy, outcomes can be improved and lives can be saved.

Histopathological Study on Collagen in Full-Thickness Wound Healing in Fraser's Dolphins (Lagenodelphis hosei).

Fraser's dolphins (Lagenodelphis hosei) possess great healing abilities. Their skin composition can be restored after wounding, including collagen spacing, orientation, and bundle thickness. However, it remains unclear how collagens are involved in the wound-healing process and eventually regain normality in Fraser's dolphins. Learned from the other two scarless healing animals, changes in type III/I collagen composition are believed to modulate the wound healing process and influence the scarring or scarless fate determination in human fetal skin and spiny mouse skin. In the current study, Herovici's, trichrome, and immunofluorescence staining were used on normal and wounded skin samples in Fraser's dolphins. The results suggested that type I collagens were the main type of collagens in the normal skin of Fraser's dolphins, while type III collagens were barely seen. During the wound healing process, type III collagens showed at early wound healing stages, and type I collagen increased in the mature healed wound. In an early healed wound, collagens were organized in a parallel manner, showing a transient hypertrophic-like scar, and eventually restored to normal collagen configuration and adipocyte distribution in the mature healed wound. The remarkable ability to remove excessive collagens merits further investigation to provide new insights into clinical wound management.

Molecular and Cellular Characterization of Avian Reticulate Scales Implies the Evo-Devo Novelty of Skin Appendages in Foot Sole.

Among amniotic skin appendages, avian feathers and mammalian hairs protect their stem cells in specialized niches, located in the collar bulge and hair bulge, respectively. In chickens and alligators, label retaining cells (LRCs), which are putative stem cells, are distributed in the hinge regions of both avian scutate scales and reptilian overlapping scales. These LRCs take part in scale regeneration. However, it is unknown whether other types of scales, for example, symmetrically shaped reticulate scales, have a similar way of preserving their stem cells. In particular, the foot sole represents a special interface between animal feet and external environments, with heavy mechanical loading. This is different from scutate-scale-covered metatarsal feet that function as protection. Avian reticulate scales on foot soles display specialized characteristics in development. They do not have a placode stage and lack ß-keratin expression. Here, we explore the molecular and cellular characteristics of avian reticulate scales. RNAscope analysis reveals different molecular profiles during surface and hinge determination compared with scutate scales. Furthermore, reticulate scales express Keratin 15 (K15) sporadically in both surface- and hinge-region basal layer cells, and LRCs are not localized. Upon wounding, the reticulate scale region undergoes repair but does not regenerate. Our results suggest that successful skin appendage regeneration requires localized stem cell niches to guide regeneration.

Risk Factors of Language Delay at Two Years of Corrected Age among Very-Low-Birth-Weight Preterm Infants: A Population-Based Study.

Language delays are often underestimated in very-low-birth-weight (VLBW) preterm infants. We aimed to identify the risk factors of language delay at two years of corrected age in this vulnerable population. VLBW infants, who were assessed at two years of corrected age using the Bayley Scale of Infant Development, third edition, were included using a population-based cohort database. Language delay was defined as mild to moderate if the composite score was between 70 and 85 and severe if the score was < 70. Multivariable logistic regression analysis was used to identify the perinatal risk factors associated with language delay. The study comprised 3797 VLBW preterm infants; 678 (18%) had a mild to moderate delay and 235 (6%) had a severe delay. After adjusting for confounding factors, low maternal education level, low maternal socioeconomic status, extremely low birth weight, male sex, and severe intraventricular hemorrhage (IVH) and/or cystic periventricular leukomalacia (PVL) were found to be significantly associated with both mild to moderate and severe delays. Resuscitation at delivery, necrotizing enterocolitis, and patent ductus arteriosus requiring ligation showed significant associations with severe delay. The strongest factors predicting both mild to moderate and severe language delays were the male sex and severe IVH and/or cystic PVL; thus, early targeted intervention is warranted in these populations.

Upper-Arm Photoplethysmographic Sensor with One-Time Calibration for Long-Term Blood Pressure Monitoring.

Wearable cuffless photoplethysmographic blood pressure monitors have garnered widespread attention in recent years; however, the long-term performance values of these devices are questionable. Most cuffless blood pressure monitors require initial baseline calibration and regular recalibrations with a cuffed blood pressure monitor to ensure accurate blood pressure estimation, and their estimation accuracy may vary over time if left uncalibrated. Therefore, this study assessed the accuracy and long-term performance of an upper-arm, cuffless photoplethysmographic blood pressure monitor according to the ISO 81060-2 standard. This device was based on a nonlinear machine-learning model architecture with a fine-tuning optimized method. The blood pressure measurement protocol followed a validation procedure according to the standard, with an additional four weekly blood pressure measurements over a 1-month period, to assess the long-term performance values of the upper-arm, cuffless photoplethysmographic blood pressure monitor. The results showed that the photoplethysmographic signals obtained from the upper arm had better qualities when compared with those measured from the wrist. When compared with the cuffed blood pressure monitor, the means ± standard deviations of the difference in BP at week 1 (baseline) were -1.36 ± 7.24 and -2.11 ± 5.71 mmHg for systolic and diastolic blood pressure, respectively, which met the first criterion of ≤5 ± ≤8.0 mmHg and met the second criterion of a systolic blood pressure ≤ 6.89 mmHg and a diastolic blood pressure ≤ 6.84 mmHg. The differences in the uncalibrated blood pressure values between the test and reference blood pressure monitors measured from week 2 to week 5 remained stable and met both criteria 1 and 2 of the ISO 81060-2 standard. The upper-arm, cuffless photoplethysmographic blood pressure monitor in this study generated high-quality photoplethysmographic signals with satisfactory accuracy at both initial calibration and 1-month follow-ups. This device could be a convenient and practical tool to continuously measure blood pressure over long periods of time.

Transition from natal downs to juvenile feathers: conserved regulatory switches in Neoaves.

The transition from natal downs for heat conservation to juvenile feathers for simple flight is a remarkable environmental adaptation process in avian evolution. However, the underlying epigenetic mechanism for this primary feather transition is mostly unknown. Here we conducted time-ordered gene co-expression network construction, epigenetic analysis, and functional perturbations in developing feather follicles to elucidate four downy-juvenile feather transition events. We discovered that LEF1 works as a key hub of Wnt signaling to build rachis and converts radial downy to bilateral symmetry. Extracellular matrix reorganization leads to peripheral pulp formation, which mediates epithelial -mesenchymal interactions for branching morphogenesis. ACTA2 compartments dermal papilla stem cells for feather cycling. Novel usage of scale keratins strengthens feather sheath with SOX14 as the epigenetic regulator. We found this primary feather transition largely conserved in chicken (precocious) and zebra finch (altricial) and discussed the possibility that this evolutionary adaptation process started in feathered dinosaurs.