Growth-phase-dependent control of rRNA synthesis in Saccharomyces cerevisiae.

Saccharomyces cerevisiae is one of the most well-studied model organisms used in the scientific community. Its ease of manipulation, accessible growth conditions, short life cycle, and conserved eukaryotic metabolic pathways make it a useful model organism. Consequently, yeast has been used to investigate a myriad of phenomena, from microbial to human studies. Most of the research performed using this model organism utilizes yeast cell populations when they are growing exponentially, a growth phase aptly termed exponential or log phase. However, log phase encompasses several yeast generations and ranges several hours of yeast growth, meaning that there is a potential for variability during this "homogenous" growth phase. Cells in log phase require robust ribosome biogenesis to support their rapid growth and cell division. Interestingly, during log phase, ribosomal RNA (rRNA) synthesis (which is the first and rate limiting step in ribosome biosynthesis) has been shown to decrease prior to growth rate decline in stationary phase. In this study, we utilized several genomic and biochemical methods to elucidate the relationship between subphases of log phase and rRNA synthesis. Our results indicate that as yeast cells progress through subphases of log growth, both polymerase I transcription and rRNA processing are repressed. Overall, this study establishes a growth-phase-dependent control of rRNA synthesis that unexpectedly begins prior to the switch to stationary phase (i.e., pre-diauxic shift) as a putative mechanism of anticipating nutrient starvation.IMPORTANCESaccharomyces cerevisiae is a ubiquitously used model organism in a wide range of scientific research fields. The conventional practice when performing yeast studies is to investigate its properties during logarithmic growth phase. This growth phase is defined as the period during which the cell population doubles at regular intervals, and nutrients are not limiting. However, this growth phase lasts hours and encompasses several yeast cell generations which consequently introduce heterogeneity to log growth phase depending on their time of harvest. This study reveals significant changes in the transcriptomic landscape even in early stages of exponential growth. The overall significance of this work is the revelation that even the seemingly homogenous log growth phase is far more diverse than was previously believed.

Gene expression analysis of Aquaporin genes in ruminants during growth phase in response to heat stress.

Aquaporins (AQPs) are trans-membrane protein involved in water transport and different cellular functions such as cell adhesion, signalling and proliferation. These membrane proteins are essential for key physiological functions such as organ development, osmoregulation, tissue regeneration and metabolism. The regulation of AQP5 gene expression in ruminants during growth phase has not been analysed in-vivo. Therefore, the gene expression pattern was analysed in Jamunapari goats during 3 months to 12 month of age and adult age group in response to heat stress. The genotyping of the AQP5 gene was carried out by High-Resolution Melting (HRM) in four different goat breeds, which indicated four distinct genotypes in the population. The nucleotide diversity for the AQP5 gene ranged from 0.315 and 0.524 across the breeds. Additionally, a close evolutionary relationship between AQP5 and the HSP70 gene was observed, indicating a shared pathway for heat stress regulation. The m-RNA expression level of AQP5 at 3, 9, 12 month and adult age group exhibited 47.24, 1140, 43.17 and 12.55-fold higher expression than control. The m-RNA expression level of the AQP5 gene was up-regulated and significantly higher (P < 0.05) at 9-month age as compared to the other age groups. Heat stress phenotypes were classified based on respiration rate and heart rate, and the m-RNA expression of AQP5 was higher in heat stress-susceptible (HSS) individuals than heat stress-tolerant (HST) individuals at 3, 9, and 12 months of age. The AQP5 plays a significant role in thermoregulation during growth phases in response to heat stress in goats, however, it is required to understand the role of aquaporins at cellular level as well as to establish the association with production performance in ruminant system in-vivo.

Native Biocrust Cyanobacteria Strains Showing Antagonism against Three Soilborne Pathogenic Fungi.

The biocontrol potential of three native soil cyanobacteria from biological soil crusts (Nostoc commune, Scytonema hyalinum, and Tolypothrix distorta) was tested by means of in vitro mycelial growth inhibition assays for eighteen cyanobacteria-based products against three phytopathogenic soilborne fungi (Phytophthora capsici, Pythium aphanidermatum, and Fusarium oxysporum f. sp. radicis-cucumerinum). Three cyanobacteria-based production factors were considered: (i) cyanobacterium strain, (ii) cyanobacterial culture growth phase, and (iii) different post-harvest treatments: raw cultures, cyanobacterial filtrates, and cyanobacterial extracts. Results showed that any of the factors considered are key points for successfully inhibiting fungal growth. N. commune showed the highest growth inhibition rates for the three phytopathogens; stationary phase treatments produced higher inhibition percentages than logarithmic ones; and all the post-harvest treatments of N. commune at the stationary phase inhibited the growth of P. capsici, up to 77.7%. Thus, N. commune products were tested in planta against P. capsici, but none of the products showed efficacy in delaying the onset nor reducing the damage due to P. capsici, demonstrating the complexity of the in planta assay's success and encouraging further research to design an appropriate scaling up methodology.

From the Microbiome to the Electrome: Implications for the Microbiota-Gut-Brain Axis.

The gut microbiome plays a fundamental role in metabolism, as well as the immune and nervous systems. Microbial imbalance (dysbiosis) can contribute to subsequent physical and mental pathologies. As such, interest has been growing in the microbiota-gut-brain brain axis and the bioelectrical communication that could exist between bacterial and nervous cells. The aim of this study was to investigate the bioelectrical profile (electrome) of two bacterial species characteristic of the gut microbiome: a Proteobacteria Gram-negative bacillus Escherichia coli (E. coli), and a Firmicutes Gram-positive coccus Enterococcus faecalis (E. faecalis). We analyzed both bacterial strains to (i) validate the fluorescent probe bis-(1,3-dibutylbarbituric acid) trimethine oxonol, DiBAC4(3), as a reliable reporter of the changes in membrane potential (Vmem) for both bacteria; (ii) assess the evolution of the bioelectric profile throughout the growth of both strains; (iii) investigate the effects of two neural-type stimuli on Vmem changes: the excitatory neurotransmitter glutamate (Glu) and the inhibitory neurotransmitter γ-aminobutyric acid (GABA); (iv) examine the impact of the bioelectrical changes induced by neurotransmitters on bacterial growth, viability, and cultivability using absorbance, live/dead fluorescent probes, and viable counts, respectively. Our findings reveal distinct bioelectrical profiles characteristic of each bacterial species and growth phase. Importantly, neural-type stimuli induce Vmem changes without affecting bacterial growth, viability, or cultivability, suggesting a specific bioelectrical response in bacterial cells to neurotransmitter cues. These results contribute to understanding the bacterial response to external stimuli, with potential implications for modulating bacterial bioelectricity as a novel therapeutic target.

SPEED-MODE cell line development (CLD): Reducing Chinese hamster ovary (CHO) CLD timelines via earlier suspension adaptation and maximizing time spent in the exponential growth phase.

Chinese hamster ovary (CHO) cells are the preferred system for expression of therapeutic proteins and the majority of all biotherapeutics are being expressed by these cell lines. CHO expression systems are readily scalable, resistant to human adventitious agents, and have desirable post-translational modifications, such as glycosylation. Regardless, drug development as a whole is a very costly, complicated, and time-consuming process. Therefore, any improvements that result in reducing timelines are valuable and can provide patients with life-saving drugs earlier. Here we report an effective method (termed SPEED-MODE, herein) to speed up the Cell line Development (CLD) process in a targeted integration (TI) CHO CLD system. Our findings show that (1) earlier single cell cloning (SCC) of transfection pools, (2) speeding up initial titer screening turnaround time, (3) starting suspension adaptation of cultures sooner, and (4) maximizing the time CHO cultures spend in the exponential growth phase can reduce CLD timelines from ~4 to ~3 months. Interestingly, SPEED-MODE timelines closely match the theoretical minimum timeline for CHO CLD assuming that CHO cell division is the rate limiting factor. Clones obtained from SPEED-MODE CLD yielded comparable titer and product quality to those obtained via a standard CLD process. Hence, SPEED-MODE CLD is advantageous for manufacturing biotherapeutics in an industrial setting as it can significantly reduce CLD timelines without compromising titer or product quality.

Dynamic Simulation of the Leaf Mass per Area (LMA) in Multilayer Crowns of Young Larix principis-rupprechtii.

Leaf mass per area (LMA) is a key structural parameter that reflects the functional traits of leaves and plays a vital role in simulating the material and energy cycles of plant ecosystems. In this study, vertical whorl-by-whorl sampling of LMA was conducted in a young Larix principis-rupprechtii plantation during the growing season at the Saihanba Forest Farm. The vertical and seasonal variations in LMA were analysed. Subsequently, a predictive model of LMA was constructed. The results revealed that the LMA varied significantly between different crown whorls and growing periods. In the vertical direction of the crown, the LMA decreased with increasing crown depth, but the range of LMA values from the tree top to the bottom was, on average, 30.4 g/m2, which was approximately 2.5 times greater in the fully expanded phase than in the early leaf-expanding phase. During different growing periods, the LMA exhibited an allometric growth trend that increased during the leaf-expanding phase and then tended to stabilize. However, the range of LMA values throughout the growing period was, on average, 40.4 g/m2. Among the univariate models, the leaf dry matter content (LDMC) performed well (adjusted determination coefficient (Ra2) = 0.45, root mean square error (RMSE) = 13.48 g/m2) in estimating the LMA. The correlation between LMA and LDMC significantly differed at different growth stages and at different vertical crown whorls. The dynamic predictive model of LMA constructed with the relative depth in the crown (RDINC) and date of the year (DOY) as independent variables was reliable in both the assessments (Ra2 = 0.68, RMSE = 10.25 g/m2) and the validation (absolute mean error (MAE) = 8.05 g/m2, fit index (FI) = 0.682). Dynamic simulations of crown LMA provide a basis for elucidating the mechanism of crown development and laying the foundation for the construction of an ecological process model.

Dynamic Protein Phosphorylation in Streptococcus pyogenes during Growth, Stationary Phase, and Starvation.

Phosphorylation of proteins at serine, threonine, and tyrosine residues plays an important role in physiological processes of bacteria, such as cell cycle, metabolism, virulence, dormancy, and stationary phase functions. Little is known about the targets and dynamics of protein phosphorylation in Streptococcus pyogenes, which possesses a single known transmembrane serine/threonine kinase belonging to the class of PASTA kinases. A proteomics and phosphoproteomics workflow was performed with S. pyogenes serotype M49 under different growth conditions, stationary phase, and starvation. The quantitative analysis of dynamic phosphorylation, which included a subset of 463 out of 815 identified phosphorylation sites, revealed two main types of phosphorylation events. A small group of phosphorylation events occurred almost exclusively at threonine residues of proteins related to the cell cycle and was enhanced in growing cells. The majority of phosphorylation events occurred during stationary phase or starvation, preferentially at serine residues. PASTA kinase-dependent cell cycle regulation processes found in related bacteria are conserved in S. pyogenes. Increased protein phosphorylation during the stationary phase has also been described for some other bacteria, and could therefore be a general feature in the physiology of bacteria, whose functions and the kinases involved need to be elucidated in further analyses.

Promoter engineering enables precise metabolic regulation towards efficient ß-elemene production in Ogataea polymorpha.

Precisely controlling gene expression is beneficial for optimizing biosynthetic pathways for improving the production. However, promoters in nonconventional yeasts such as Ogataea polymorpha are always limited, which results in incompatible gene modulation. Here, we expanded the promoter library in O. polymorpha based on transcriptional data, among which 13 constitutive promoters had the strengths ranging from 0-55% of PGAP, the commonly used strong constitutive promoter, and 2 were growth phase-dependent promoters. Subsequently, 2 hybrid growth phase-dependent promoters were constructed and characterized, which had 2-fold higher activities. Finally, promoter engineering was applied to precisely regulate cellular metabolism for efficient production of ß-elemene. The glyceraldehyde-3-phosphate dehydrogenase gene GAP was downregulated to drive more flux into pentose phosphate pathway (PPP) and then to enhance the supply of acetyl-CoA by using phosphoketolase-phosphotransacetylase (PK-PTA) pathway. Coupled with the phase-dependent expression of synthase module (ERG20∼LsLTC2 fusion), the highest titer of 5.24 g/L with a yield of 0.037 g/(g glucose) was achieved in strain YY150U under fed-batch fermentation in shake flasks. This work characterized and engineered a series of promoters, that can be used to fine-tune genes for constructing efficient yeast cell factories.

Three distinct metabolic phases of polychlorinated biphenyls/biphenyl degrader Acidovorax sp. KKS102 in nutrient broth.

Acidovorax sp. KKS102 is a beta-proteobacterium capable of degrading polychlorinated biphenyls (PCBs). In this study, we examined its growth in liquid nutrient broth supplemented with different carbon sources. KKS102 had at least 3 distinct metabolic phases designated as metabolic phases 1-3, with phase 2 having 2 sub-phases. For example, succinate, fumarate, and glutamate, known to repress the PCB/biphenyl catabolic operon in KKS102, were utilized in phase 1, while acetate, arabinose, and glycerol in phase 2, and glucose and mannose in phase 3. We also showed that the BphQ response regulator mediating catabolite control in KKS102, whose expression level increased moderately through the growth, plays important roles in carbon metabolism in phases 2 and 3. Our study elucidates the hierarchical growth of KKS102 in nutrient-rich media. This insight is crucial for studies exploiting microbial biodegradation capabilities and advancing studies for catabolite regulation mechanisms.

Phenotypic and transcriptome profiling of spikes reveals the regulation of light regimens on spike growth and fertile floret number in wheat.

The spike growth phase is critical for the establishment of fertile floret (grain) numbers in wheat (Triticum aestivum L.). Then, how to shorten the spike growth phase and increase grain number synergistically? Here, we showed high-resolution analyses of floret primordia (FP) number, morphology and spike transcriptomes during the spike growth phase under three light regimens. The development of all FP in a spike could be divided into four distinct stages: differentiation (Stage I), differentiation and morphology development concurrently (Stage II), morphology development (Stage III), and polarization (Stage IV). Compared to the short photoperiod, the long photoperiod shortened spike growth and stimulated early flowering by shortening Stage III; however, this reduced assimilate accumulation, resulting in fertile floret loss. Interestingly, long photoperiod supplemented with red light shortened the time required to complete Stages I-II, then raised assimilates supply in the spike and promoted anther development before polarization initiation, thereby increasing fertile FP number during Stage III, and finally maintained fertile FP development during Stage IV until they became fertile florets via a predicted dynamic gene network. Our findings proposed a light regimen, critical stages and candidate regulators that achieved a shorter spike growth phase and a higher fertile floret number in wheat.

Regulatory mechanism of the miR172e-LbrAP2 module during the vegetative growth phase transition in Lilium.

MAIN CONCLUSION: It was proved for the first time that the miR172e-LbrAP2 module regulated the vegetative growth phase transition in Lilium, which provided a new approach to shorten the juvenile stage of Lilium, improved the reproduction rate, and reduced the propagation cost of Lilium commercial bulbs. Lilium is an ornamental bulb plant that takes at least 3 years to cultivate into commercial seed bulbs under natural conditions. The aim of this study was to shorten the Lilium expansion cycle. In this study, the growth cycle of lily tubers induced by low temperature of 15 °C was significantly shorter than that of tubers grown at a conventional temperature. Quantitative real-time PCR analysis showed that the expression patterns of miR172e and LbrAP2 were negatively correlated. GUS histochemical staining confirmed that miR172e and LbrAP2 in tobacco leaves interacted with each other after co-transformation. The shear sites of miR172e and its target gene, LbrAP2, upon binding, were identified by RLM 5' RACE analysis. In addition, miR172e and LbrAP2 showed opposite expression patterns after the transformation of Arabidopsis. miR172e overexpression accelerated the transition from juvenile to adult plants, whereas LbrAP2 overexpression inhibited this process, thus indicating that miR172e negatively regulated the target gene LbrAP2. Upregulation of the transcription factor LbrAP2 delayed the phase transition of plants, whereas miR172 inhibited the transcriptional translation of LbrAP2, thereby accelerating the phase transition. Low-temperature treatment of Lilium bulbs can shorten Lilium development, which provides a new approach to accelerating Lilium commercial bulb breeding and reducing breeding costs.

The Regulatory Functions of the Multiple Alternative Sigma Factors RpoE, RpoHI, and RpoHII Depend on the Growth Phase in Rhodobacter sphaeroides.

Bacterial growth, under laboratory conditions or in a natural environment, goes through different growth phases. Some gene expressions are regulated with respect to the growth phase, which allows bacteria to adapt to changing conditions. Among them, many gene transcriptions are controlled by RpoHI or RpoHII in Rhodobacter sphaeroides. In a previous study, it was proven that the alternative sigma factors, RpoE, RpoHI, and RpoHII, are the major regulators of oxidative stress. Moreover, the growth of bacteria reached a stationary phase, and following the outgrowth, rpoE, rpoHI, and rpoHII mRNAs increased with respect to the growth phase. In this study, we demonstrated the regulatory function of alternative sigma factors in the rsp_0557 gene. The gene rsp_0557 is expressed with respect to the growth phase and belongs to the RpoHI/RpoHII regulons. Reporter assays showed that the antisigma factor ChrR turns on or over the RpoE activity to regulate rsp_0557 expression across the growth phase. In the exponential phase, RpoHII and sRNA Pos19 regulate the expression of rsp_0557 to an appropriate level under RpoE control. In the stationary phase, RpoHI and Pos19 stabilize the transcription of rsp_0557 at a high level. During outgrowth, RpoHI negatively regulates the transcription of rsp_0557. Taken together, our data indicate that these regulators are recruited by cells to adapt to or survive under different conditions throughout the growth phase. However, they still did not display all of the regulators involved in growth phase-dependent regulation. More research is still needed to learn more about the interaction between the regulators and the process of adapting to changed growth conditions and environments.

Circadian clock does not play an essential role in daylength measurement for growth-phase transition in Marchantia polymorpha.

Daylength is perceived as a seasonal cue to induce growth-phase transition at a proper time of a year. The core of the mechanism of daylength measurement in angiosperms lies in the circadian clock-controlled expression of regulators of growth-phase transition. However, the roles of the circadian clock in daylength measurement in basal land plants remain largely unknown. In this study, we investigated the contribution of circadian clock to daylength measurement in a basal land plant, the liverwort Marchantia polymorpha. In M. polymorpha, transition from vegetative to reproductive phase under long-day conditions results in differentiation of sexual branches called gametangiophores which harbor gametangia. First, we showed that a widely used wild-type accession Takaragaike-1 is an obligate long-day plant with a critical daylength of about 10 hours and requires multiple long days. Then, we compared the timing of gametangiophore formation between wild type and circadian clock mutants in long-day and short-day conditions. Mutations in two clock genes, MpTIMING OF CAB EXPRESSION 1 and MpPSEUDO-RESPONSE REGULATOR, had no significant effects on the timing of gametangiophore formation. In addition, when M. polymorpha plants were treated with a chemical which lengthens circadian period, there was no significant effect on the timing of gametangiophore formation, either. We next observed the timing of gametangiophore formation under various non-24-h light/dark cycles to examine the effect of phase alteration in circadian rhythms. The results suggest that daylength measurement in M. polymorpha is based on the relative amount of light and darkness within a cycle rather than the intrinsic rhythms generated by circadian clock. Our findings suggest that M. polymorpha has a daylength measurement system which is different from that of angiosperms centered on the circadian clock function.

Is a lower-toxicity strain of Microcystis aeruginosa really less toxic?

Some well-known hazards of blooming cyanobacteria are caused by toxic metabolites such as microcystins (MCs), though many other bioactive chemicals of unknown toxicity are present in their exudates. It is also unclear whether toxicity of cyanobacterial cells depends on growth phases in the life cycle. In this study, we compared toxicity to Daphnia magna of Microcystis aeruginosa - a common cyanobacterial species - exudates (MaE) from two MC-producing strains over both exponential growth and stationary phases in acute and chronic experiments. Specifically, we assessed mitochondrial dysfunction, oxidative stress and lipid peroxidation, and filtering activity and heartbeat rate of Daphnia exposed to MaE. All MaE treatments induced common characteristics of Microcystis toxicity including disorder in the mitochondrial membrane and aberrant heart rate. MaE from cells at stationary growth phase were more toxic than those at exponential phase. Surprisingly, the MC-lower strain had higher toxicity than MC-higher one. Microcystis at different stage of blooms may differentially affect waterfleas owing to variable MaE-induced physiological dysfunction, abundance and grazing rate. Our study suggested that Microcystis strains with lower microcystin-producing ability might release other detrimental chemicals and should not be ignored in harmful bloom monitoring.

The optimal control chart selection for monitoring COVID-19 phases: a case study of daily deaths in the USA.

Epidemiologists frequently adopt statistical process control tools, like control charts, to detect changes in the incidence or prevalence of a specific disease in real time, thereby protecting against outbreaks and emergent health concerns. Control charts have proven essential in instantly identifying fluctuations in infection rates, spotting emerging patterns, and enabling timely reaction measures in the context of COVID-19 monitoring. This study aims to review and select an optimal control chart in epidemiology to monitor variations in COVID-19 deaths and understand pandemic mortality patterns. An essential aspect of the present study is selecting an appropriate monitoring technique for distinct deaths in the USA in seven phases, including pre-growth, growth, and post-growth phases. Stage-1 evaluated control chart applications in epidemiology departments of 12 countries between 2000 and 2022. The study assessed various control charts and identified the optimal one based on maximum shift detection using sample data. This study considered at Shewhart ($\bar X$, $R$, $C$) control charts and exponentially weighted moving average (EWMA) control chart with smoothing parameters λ = 0.25, 0.5, 0.75, and 1 were all investigated in this study. In Stage-2, we applied the EWMA control chart for monitoring because of its outstanding shift detection capabilities and compatibility with the present data. Daily deaths have been monitored from March 2020 to February 2023. Control charts in epidemiology show growing use, with the USA leading at 42% applications among top countries. During the application on COVID-19 deaths, the EWMA chart accurately depicted mortality dynamics from March 2020 to February 2022, indicating six distinct stages of death. The third and fifth waves were extremely catastrophic, resulting in a considerable loss of life. Significantly, a persistent sixth wave appeared from March 2022 to February 2023. The EWMA map effectively determined the peaks associated with each wave by thoroughly examining the time and amount of deaths, providing vital insights into the pandemic's progression. The severity of each wave was measured by the average number of deaths $W5(1899)\,\gt\,W3(1881)\,\gt\,W4(1393)\,\gt\,W1(1036)\,\gt\,W2(853)\,\gt\,(W6(473)$. The USA entered a seventh phase (6th wave) from March 2022 to February 2023, marked by fewer deaths. While reassuring, it remains crucial to maintain vaccinations and pandemic control measures. Control charts enable early detection of daily COVID-19 deaths, providing a systematic strategy for government and medical staff. Incorporating the EWMA chart for monitoring immunizations, cases, and deaths is recommended.

Why Do These Yeasts Smell So Good? Volatile Organic Compounds (VOCs) Produced by Malassezia Species in the Exponential and Stationary Growth Phases.

Malassezia synthesizes and releases volatile organic compounds (VOCs), small molecules that allow them to carry out interaction processes. These lipid-dependent yeasts belong to the human skin mycobiota and are related to dermatological diseases. However, knowledge about VOC production and its function is lacking. This study aimed to determine the volatile profiles of Malassezia globosa, Malassezia restricta, and Malassezia sympodialis in the exponential and stationary growth phases. The compounds were separated and characterized in each growth phase through headspace solid-phase microextraction (HS-SPME) and gas chromatography-mass spectrometry (GC-MS). We found a total of 54 compounds, 40 annotated. Most of the compounds identified belong to alcohols and polyols, fatty alcohols, alkanes, and unsaturated aliphatic hydrocarbons. Unsupervised and supervised statistical multivariate analyses demonstrated that the volatile profiles of Malassezia differed between species and growth phases, with M. globosa being the species with the highest quantity of VOCs. Some Malassezia volatiles, such as butan-1-ol, 2-methylbutan-1-ol, 3-methylbutan-1-ol, and 2-methylpropan-1-ol, associated with biological interactions were also detected. All three species show at least one unique compound, suggesting a unique metabolism. The ecological functions of the compounds detected in each species and growth phase remain to be studied. They could interact with other microorganisms or be an important clue in understanding the pathogenic role of these yeasts.

Is It Time to Supersede the Diagnostic Term "Melanoma In Situ with Regression?" A Narrative Review.

Traditionally, the term melanoma in situ (MIS) is used to designate a horizontal (radial) growth phase of malignant melanoma (MM) in which there is no histological evidence of any invasion (or microinvasion) of neoplastic melanocytic cells into the superficial or papillary dermis. In daily dermatopathological practice, we are faced with misleading definitions, such as "melanoma in situ with regression," which risk affecting homogeneity for comparison purposes of pathological reports of malignant melanoma. The authors conducted a literature review using PubMed and Web of Science (WoS) as the main databases and using the following keywords: "Malignant Melanoma in situ" or "Melanoma in situ" and "regression" and/or "radial growth phase regression." A total of 213 articles from both analyzed databases were retrieved; finally, only eight articles in English were considered suitable for the chosen inclusion criteria. In consideration of the absence of studies with large case series, of reviews with meta-analyses, and, therefore, of a broad scientific consensus, expressions including "melanoma in situ with regression" should be avoided in the histopathological report. Instead, they should be replaced with clearer and more exhaustive definitions.

Growth stage-related biomass, pigments, and biochemical composition of Stichococcus bacillaris, Synechococcus sp., and Trentepohlia aurea isolated from Gua Tempurung, a cave in Malaysia.

As part of the lampenflora that inhabit limestone caves, microalgae play an important role in cave ecosystems but are understudied in tropical ecoregions. In the present study, the dominant eukaryotic and prokaryotic microalgae identified in lampenflora samples collected from Gua Tempurung, a cave in Malaysia, and growth stage-related microalgal attributes were determined. Stichococcus bacillaris, Synechococcus sp., and Trentepohlia aurea were selected and cultured in Bold's Basal Medium (S. bacillaris and T. aurea) or BG-11 medium (Synechococcus sp.) under laboratory conditions. The highest specific growth rate (0.72 ± 0.21 day-1) and dry weight (0.11 ± 0.04 mg L-1) were recorded in S. bacillaris in the early stationary phase. Trentepohlia aurea and Synechococcus sp. had the highest ash-free dry weight and total ash percentage (11.18 ± 4.64 mg L-1 and 8.55% ± 6.73%, respectively) in the early stationary phase. Stichococcus bacillaris had the highest moisture content (84.26% ± 0.64%) in the exponential phase. Chlorophylls a and b were highest in the early stationary phase in T. aurea (0.706 ± 0.40 mg L-1 and 1.094 ± 0.589 mg L-1, respectively). Carotenoid levels were highest in Synechococcus sp. in the early stationary stage (0.07 ± 0.02 mg L-1). Lipids were the major biochemical compound identified at the highest levels in Synechococcus sp. (67.87% ± 7.75%) in the early stationary phase, followed by protein recorded at the highest levels in T. aurea (57.99% ± 4.99%) in the early stationary phase. Carbohydrates were the compound identified least often with the highest recorded levels found in T. aurea (9.94% ± 0.49%) in the late stationary phase. Biomass, pigments, and biochemical accumulation varied at different growth stages in the studied microalgae, and this variation was species-specific. The present study provides a benchmark for the growth phases of aerophytic cave microalgae, which will be useful for determining their optimum harvest time and obtaining biochemical compounds of interest.

Analysis of Corn Yield Prediction Potential at Various Growth Phases Using a Process-Based Model and Deep Learning.

Early and accurate prediction of grain yield is of great significance for ensuring food security and formulating food policy. The exploration of key growth phases and features is beneficial to improving the efficiency and accuracy of yield prediction. In this study, a hybrid approach using the WOFOST model and deep learning was developed to forecast corn yield, which analysed yield prediction potential at different growth phases and features. The World Food Studies (WOFOST) model was used to build a comprehensive simulated dataset by inputting meteorological, soil, crop and management data. Different feature combinations at various growth phases were designed to forecast yield using machine learning and deep learning methods. The results show that the key features of corn's vegetative growth stage and reproductive growth stage were growth state features and water-related features, respectively. With the continuous advancement of the crop growth stage, the ability to predict yield continued to improve. Especially after entering the reproductive growth stage, corn kernels begin to form, and the yield prediction performance is significantly improved. The performance of the optimal yield prediction model in flowering (R2 = 0.53, RMSE = 554.84 kg/ha, MRE = 8.27%), in milk maturity (R2 = 0.89, RMSE = 268.76 kg/ha, MRE = 4.01%), and in maturity (R2 = 0.98, RMSE = 102.65 kg/ha, MRE = 1.53%) were given. Thus, our method improves the accuracy of yield prediction, and provides reliable analysis results for predicting yield at various growth phases, which is helpful for farmers and governments in agricultural decision making. This can also be applied to yield prediction for other crops, which is of great value to guide agricultural production.